Datasets:

---

DanielPFlorian

/

Transformers-Github-Issues

like 0

[]

[]

[]

[]

[]

[ "I just noticed the same.\r\n\r\nIt seems that you have to include the `labels` parameter as well to get the predictions for your `decoder_input_ids`. You didn't have to do this in versions prior to 3.0, so it appears as if something has changed so that it's required now.\r\n\r\nMaybe @sshleifer knows since I think he's been doing quite a bit of work on the summarization bits as of late.", "Great catch. I think you are spot on that the API changed a bit in 3.0. We should have documented it better.\r\n\r\nIf you pass `use_cache=False` to `model() this problem goes away. (use_cache is set to true by default to speed up seq2seq tasks).\r\nYou can also pass `use_cache=False` to `from_pretrained`, as shown below:\r\n\r\n```python\r\ntokenizer = BartTokenizer.from_pretrained('facebook/bart-large')\r\nmodel = BartForConditionalGeneration.from_pretrained('facebook/bart-large', use_cache=False)\r\ninputs = tokenizer.encode(\" Hello, my dog is cute\", return_tensors=\"pt\")\r\ndecoder_input = tokenizer.encode(\" Oh! I don't know that you have dog! How is it?\", return_tensors=\"pt\")\r\noutput = model(input_ids=inputs,decoder_input_ids=decoder_input)[0]\r\nassert output.shape[1] ==17 # passes\r\n```", "> Great catch. I think you are spot on that the API changed a bit in 3.0. We should have documented it better.\r\n> \r\n> If you pass `use_cache=False` to `model() this problem goes away. (use_cache is set to true by default to speed up seq2seq tasks). You can also pass `use_cache=False`to`from_pretrained`, as shown below:\r\n> \r\n> ```python\r\n> tokenizer = BartTokenizer.from_pretrained('facebook/bart-large')\r\n> model = BartForConditionalGeneration.from_pretrained('facebook/bart-large', use_cache=False)\r\n> inputs = tokenizer.encode(\" Hello, my dog is cute\", return_tensors=\"pt\")\r\n> decoder_input = tokenizer.encode(\" Oh! I don't know that you have dog! How is it?\", return_tensors=\"pt\")\r\n> output = model(input_ids=inputs,decoder_input_ids=decoder_input)[0]\r\n> assert output.shape[1] ==17 # passes\r\n> ```\r\n\r\nThanks a lot! I think it's better to publish a post which explains differences between version 2 and 3.0 " ]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5518?src=pr&el=h1) Report\n> Merging [#5518](https://codecov.io/gh/huggingface/transformers/pull/5518?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/58cca47c16149e43d1b516623d59e3c5d97f695e&el=desc) will **decrease** coverage by `1.02%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5518?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5518 +/- ##\n==========================================\n- Coverage 77.83% 76.81% -1.03% \n==========================================\n Files 141 141 \n Lines 24634 24637 +3 \n==========================================\n- Hits 19175 18925 -250 \n- Misses 5459 5712 +253 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5518?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_t5.py](https://codecov.io/gh/huggingface/transformers/pull/5518/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190NS5weQ==) | `84.44% <100.00%> (+0.09%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/5518/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `23.62% <0.00%> (-73.11%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5518/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `26.92% <0.00%> (-68.47%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5518/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `81.09% <0.00%> (+1.37%)` | :arrow_up: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5518/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.71% <0.00%> (+1.50%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5518/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `98.76% <0.00%> (+32.51%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5518/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `94.98% <0.00%> (+74.19%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5518?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5518?src=pr&el=footer). Last update [58cca47...904fa94](https://codecov.io/gh/huggingface/transformers/pull/5518?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Thanks a lot for the review @mfuntowicz! I adjusted it to the coding style you outlined. Feel free to merge if you're happy with it.", "LGTM! Thanks @abelriboulot, great addition 👍 ", "Hey, did you happen to make a colab which shows this off? I was trying to figure out exporting T5 as ONNX a week ago, but got stuck. It seems you've fixed it though?", "@ConProgramming sure thing, I’ll share something this weekend!", "@abelriboulot Did you ever get around to making that colab? It'd help a lot. 😅", "Hey @ConProgramming, I had a very ad-hoc solution for this, therefore I worked on a PR to make the huggingface conversion compatible with all models with a compatible graph. You can take a look at it there: #5687\r\nIf you pull this version you should be able to export T5 with the following line:\r\n`python convert_graph_to_onnx.py --framework pt --model t5-base ~/test-t5/t5.onnx --check-loading --opset 12`\r\n\r\nI checked and it seems to work well! Let me know if it works for you.", "Thanks @abelriboulot, but I'm still having some issues with it... it works with t5-base, but depending on how I provide the path to my own model I get two different errors:\r\n\r\n- `!python transformers/src/transformers/convert_graph_to_onnx.py --framework pt --model \"drive/My Drive/paraphraser/t5_paraphrase/pytorch_model.bin\" onnx/paraphraser.onnx --check-loading --opset 12` : Error while converting the model: 'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte\r\n- `drive/My Drive/paraphraser/t5_paraphrase` : Error while converting the model: Model name 'drive/My Drive/paraphraser/t5_paraphrase' was not found in tokenizers model name list (t5-small, t5-base, t5-large, t5-3b, t5-11b). We assumed 'drive/My Drive/paraphraser/t5_paraphrase' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\r\n\r\nIs it designed to work with finetuned models?", "Hey @ConProgramming, it should work on fine tuned models, you can have a look at the test_onnx file as an example of this. The model path should be to the directory that contains the model (and the tokenizer in case you do not specify it). It looks like the second error relates to not being able to find a tokenizer, is it present in your directory? If you are using another directory / pretrained model you can specify it with --tokenizer\r\nIf you still have issues and it's something you can share, I'm happy to have a look and help you with this.", "@abelriboulot Adding `--tokenizer t5-base` fixed the issue and exported a model without any errors... looks like it worked, thanks again!!", "Oh awesome! Great to hear it! I might add a message to make it more obvious to the user.", "@abelriboulot \r\n\r\nI tried this (for cpu):\r\nconvert_graph_to_onnx.py --framework=pt --tokenizer=t5-base --model=t5-base onnx\\t5.onnx --check-loading --opset=12\r\n\r\n but getting error:\r\n\r\nONNX opset version set to: 12\r\nLoading pipeline (model: t5-base, tokenizer: t5-base)\r\nSome weights of T5Model were not initialized from the model checkpoint at t5-base and are newly initialized: ['encoder.embed_tokens.weight', 'decoder.embed_tokens.weight']\r\nYou should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\r\nUsing framework PyTorch: 1.5.1+cpu\r\nFound input input_ids with shape: {0: 'batch', 1: 'sequence'}\r\nFound input attention_mask with shape: {0: 'batch', 1: 'sequence'}\r\nFound output output_0 with shape: {0: 'batch', 1: 'sequence'}\r\n**Error while converting the model: 'BaseModelOutputWithPast' object has no attribute 'shape'**\r\n\r\nAm I doing something wrong here?", "Hey @oliversms, are you using the specific fork or master? I can confirm the command you submitted works on my side.", "Apologies for the delayed reply; Im actually using the fork. I beleive it may have been an env related issue. However after getting past that issue Im now running into a new issue:\r\nSpecifically on this line:\r\n[tokens = nlp.tokenizer(\"This is a sample output\", return_tensors=framework)](https://github.com/abelriboulot/transformers/blob/58cca47c16149e43d1b516623d59e3c5d97f695e/src/transformers/convert_graph_to_onnx.py#L89)\r\ngetting this error: \r\nValueError: Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length.\r\n\r\nAttempting set padding & truncation to True doesnt fix the issue.", "Hey @oliversms! It looks like you are not using the right branch. You need [this specific branch](https://github.com/abelriboulot/transformers/tree/update_convert_to_onnx) for it to work. Hope it works for you!\r\n\r\nAbel", "If anyone needs, I created a small package ([onnxt5](https://github.com/abelriboulot/onnxt5)) which lets you easily and efficiently export T5 and serve it! Feel free to raise issues, it's an alpha at the moment.", "@abelriboulot Hi, I pulled your branch and tried to convert a t5-base with \r\npython ../transformers/src/convert_graph_to_onnx.py --framework pt --model t5-base t5-base.onnx --check-loading --opset 12\r\n\r\nand still got the \"Error while converting the model: You have to specify either decoder_input_ids or decoder_inputs_embeds\" Any ideas?" ]

[ { "id": 1834056635, "node_id": "MDU6TGFiZWwxODM0MDU2NjM1", "url": "https://api.github.com/repos/huggingface/transformers/labels/Core:%20Tokenization", "name": "Core: Tokenization", "color": "FF4446", "default": false, "description": "Internals of the library; Tokenization." } ]

[ { "login": "LysandreJik", "id": 30755778, "node_id": "MDQ6VXNlcjMwNzU1Nzc4", "avatar_url": "https://avatars.githubusercontent.com/u/30755778?v=4", "gravatar_id": "", "url": "https://api.github.com/users/LysandreJik", "html_url": "https://github.com/LysandreJik", "followers_url": "https://api.github.com/users/LysandreJik/followers", "following_url": "https://api.github.com/users/LysandreJik/following{/other_user}", "gists_url": "https://api.github.com/users/LysandreJik/gists{/gist_id}", "starred_url": "https://api.github.com/users/LysandreJik/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/LysandreJik/subscriptions", "organizations_url": "https://api.github.com/users/LysandreJik/orgs", "repos_url": "https://api.github.com/users/LysandreJik/repos", "events_url": "https://api.github.com/users/LysandreJik/events{/privacy}", "received_events_url": "https://api.github.com/users/LysandreJik/received_events", "type": "User", "site_admin": false } ]

[]

[]

[]

[ "This is a back-port of https://github.com/guillaume-be/rust-bert/pull/57. I did not implement the ConversationManager as I felt it did not quite fit the general API of this library. I however added the concept of `Conversations` keeping track of past user inputs, generated responses and the history token ids. Conversations include a print option that will display the entire dialogue.\r\n\r\n```python\r\nprint(conversation)\r\n```\r\n```\r\nConversation id: 2716da3e-8cde-4071-97bc-218d88764b7b \r\nuser >> What's the last book you have read? \r\nbot >> The Last Question \r\nuser >> Why do you recommend it? \r\nbot >> It's a good book. \r\n```\r\n\r\n(ps: note that this example is the response of `DialoGPT-medium` without sampling, which is an interesting coincidence for a computer-generated response)", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5516?src=pr&el=h1) Report\n> Merging [#5516](https://codecov.io/gh/huggingface/transformers/pull/5516?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/91cb95461e438dc57555c4f57f8ce95a56328036&el=desc) will **increase** coverage by `1.49%`.\n> The diff coverage is `84.34%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5516?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5516 +/- ##\n==========================================\n+ Coverage 78.35% 79.85% +1.49% \n==========================================\n Files 146 146 \n Lines 26454 26568 +114 \n==========================================\n+ Hits 20729 21215 +486 \n+ Misses 5725 5353 -372 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5516?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/\\_\\_init\\_\\_.py](https://codecov.io/gh/huggingface/transformers/pull/5516/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9fX2luaXRfXy5weQ==) | `99.24% <ø> (ø)` | |\n| [src/transformers/pipelines.py](https://codecov.io/gh/huggingface/transformers/pull/5516/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9waXBlbGluZXMucHk=) | `79.36% <84.34%> (+0.86%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_flaubert.py](https://codecov.io/gh/huggingface/transformers/pull/5516/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9mbGF1YmVydC5weQ==) | `24.22% <0.00%> (-63.98%)` | :arrow_down: |\n| [src/transformers/tokenization\\_t5.py](https://codecov.io/gh/huggingface/transformers/pull/5516/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdDUucHk=) | `71.83% <0.00%> (-23.95%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/5516/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `71.65% <0.00%> (-23.68%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5516/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.46% <0.00%> (+0.25%)` | :arrow_up: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5516/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `97.11% <0.00%> (+0.28%)` | :arrow_up: |\n| [src/transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5516/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHMucHk=) | `90.36% <0.00%> (+0.40%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/5516/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hdXRvLnB5) | `66.66% <0.00%> (+3.63%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5516/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `98.79% <0.00%> (+34.61%)` | :arrow_up: |\n| ... and [1 more](https://codecov.io/gh/huggingface/transformers/pull/5516/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5516?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5516?src=pr&el=footer). Last update [91cb954...9734829](https://codecov.io/gh/huggingface/transformers/pull/5516?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "@patrickvonplaten Thank you so much for the detailed review! I have pushed some changes addressing most of the suggested changes.\r\n\r\nA few points still open for discussion:\r\n- I am still unsure about using the default `max_length` from the model_config, especially since the default model used for the pipeline `DialoGPT` does not give this value and it would default to a very low value.\r\n- I have updated the history truncation to take out entire spans (delimited by EOS tokens). I believe this would lead to a more natural truncation of a conversation (skip the first N turn) rather than possibly cutting an input/response in the middle\r\n- You are right that the API differs a bit from the other pipeline (although the QA pipeline also takes special inputs). Here the challenge is that the conversations are by definition stateful. I actually started the Rust implementation storing the conversations in the model itself, allowing simpler inputs to be passed on. This requires the model to be mutable, which can be problematic for multithreading. Now in Python you may not have this issue, but you may want to deploy an conversational application that scales and deploys multiple conversation pipeline workers / containers (the Rust compiler actually points out to an interesting design decision). If you make these stateful, you'll have to ensure that you always send the conversation to the correct worker which can be sub-optimal for load balancing. I believe carrying the history in the conversation itself would be easier to handle for the full system that may leverage this pipeline. Happy to change if you'd like to allow the user to pass a simpler input, but a conversation `id` would probably be required anyway. In any case happy to expose `Conversation` to the library API if the design remains as is.\r\n\r\nThanks again for the feedback - looking forward to your thoughts on these few points.", "Thanks a lot for the detailed answer @guillaume-be,\r\n\r\n1. (answering to your comment above) - exactly, I would update the config on AWS \r\n and it would then look like this:\r\n```\r\n{\r\n \"activation_function\": \"gelu_new\",\r\n \"architectures\": [\r\n \"GPT2LMHeadModel\"\r\n ],\r\n \"attn_pdrop\": 0.1,\r\n \"bos_token_id\": 50256,\r\n \"embd_pdrop\": 0.1,\r\n \"eos_token_id\": 50256,\r\n \"initializer_range\": 0.02,\r\n \"layer_norm_epsilon\": 1e-05,\r\n \"model_type\": \"gpt2\",\r\n \"n_ctx\": 1024,\r\n \"n_embd\": 1024,\r\n \"n_head\": 16,\r\n \"n_layer\": 24,\r\n \"n_positions\": 1024,\r\n \"resid_pdrop\": 0.1,\r\n \"summary_activation\": null,\r\n \"summary_first_dropout\": 0.1,\r\n \"summary_proj_to_labels\": true,\r\n \"summary_type\": \"cls_index\",\r\n \"summary_use_proj\": true,\r\n \"vocab_size\": 50257,\r\n \"task_specific_params\" : {\r\n \"dialogue\": { \r\n \"max_length\": 1000\r\n }\r\n }\r\n}\r\n```\r\n=> This way in the `__init__` of `Pipeline` the `task_specific_params` will overwrite the default params and the `max_length` will be 1000. I think this has following advantage: If the user wants to define a specific `max_length` via the model config, he could update or create a config to `model.config.task_specific_params.dialogue.max_length = 1000` and does not have to input any generate kwargs to the `__call__` function (otherwise the config would always be overwritten by 1000). As soon as we merge this PR, I can update all the DialoGPT configs with the `task_specific_params`.\r\n\r\n2. Very nice! This indeed makes more sense and should lead to good (possible never-ending chats) :-) \r\n\r\n3. I agree - I think I'm also in favor of your design choice here. Sadly, I don't have the necessary Rust knowledge to have a better understanding of the consequences of stateful vs. stateless, but it makes a lot of sense what you say! Maybe looping in @mfuntowicz here to see what he thinks :-) ", "Thanks @guillaume-be for your PR!\r\n\r\nI left a bunch of comments, but this is in good shape, can't wait to use it on https://huggingface.co/microsoft/DialoGPT-large 😄 \r\n\r\nRe. statefulness, yes, we definitely want to keep a stateless system.\r\n\r\nAs an example, the way our https://convai.huggingface.co/ demo from last year works (and probably the way our conversational widget powered by this PR will work too 😉) is, we store an array of `Message` on the client side, grow it, and send it with each request. It's text so the bandwidth is not an issue.\r\n\r\nMessage looks like:\r\n\r\n```\r\ninterface Message {\r\n\tincoming: boolean; // <- is it from bot or user\r\n\tcontent: string;\r\n}\r\n```\r\n\r\n", "LGTM", "@julien-c @patrickvonplaten I believe all comments have been addressed - please let me know if I have missed anything. Just resolved the conflict with master. Getting an error with `code quality`, not quite sure what is wrong as I did not change the torch requirement with this PR.", "Given that `patrickvonplaten` is off for one more week I believe, do you want to give this PR a last look-over @sgugger and merge if it's fine?", "@LysandreJik Thank you very much for the review. Good catch on the behaviour of the `eos` token cut-off. I have updated based on your suggestions, and added docstrings to the `Conversation` class. I have also added both `Conversation` and `ConversationalPipeline` to the top-level `__init__` for consistency with the other pipelines.", "Thanks for the PR @guillaume-be \r\nDocstrings could be improved but I'll clean up the docs in the pipelines file soon, so will take of that. For future PRs, please remember that `thing` will render thing in italics in the docs, and not in code (you have to use ``thing`` or :obj:`thing`).", "@sgugger Thank you for the review - was indeed a typo on my end. The tests got triggered again and unfortunately a hash verification on torch fails. Could you please restart the build if you have a chance?", "This is awesome, congrats everyone on shipping this! 🔥", "`test_torch_conversation` and `test_integration_torch_conversation` are broken on github actions CI. Could someone fix or delete? https://github.com/huggingface/transformers/runs/1289790225?check_suite_focus=true", "Will take a look.", "Should be fixed in https://github.com/huggingface/transformers/pull/7970" ]

[ { "id": 1838412367, "node_id": "MDU6TGFiZWwxODM4NDEyMzY3", "url": "https://api.github.com/repos/huggingface/transformers/labels/model%20card", "name": "model card", "color": "92d5f4", "default": false, "description": "Related to pretrained model cards" } ]

[]

[]

[ { "id": 1838412367, "node_id": "MDU6TGFiZWwxODM4NDEyMzY3", "url": "https://api.github.com/repos/huggingface/transformers/labels/model%20card", "name": "model card", "color": "92d5f4", "default": false, "description": "Related to pretrained model cards" } ]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5514?src=pr&el=h1) Report\n> Merging [#5514](https://codecov.io/gh/huggingface/transformers/pull/5514?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/58cca47c16149e43d1b516623d59e3c5d97f695e&el=desc) will **decrease** coverage by `1.73%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5514?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5514 +/- ##\n==========================================\n- Coverage 77.83% 76.10% -1.74% \n==========================================\n Files 141 141 \n Lines 24634 24634 \n==========================================\n- Hits 19175 18748 -427 \n- Misses 5459 5886 +427 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5514?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/5514/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `23.62% <0.00%> (-73.11%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/5514/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hbGJlcnQucHk=) | `20.49% <0.00%> (-55.49%)` | :arrow_down: |\n| [src/transformers/tokenization\\_xlm\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5514/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxtX3JvYmVydGEucHk=) | `61.90% <0.00%> (-33.34%)` | :arrow_down: |\n| [src/transformers/tokenization\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/5514/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWFyaWFuLnB5) | `68.14% <0.00%> (-25.67%)` | :arrow_down: |\n| [src/transformers/optimization\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/5514/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9vcHRpbWl6YXRpb25fdGYucHk=) | `33.33% <0.00%> (-24.33%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5514/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `81.09% <0.00%> (+1.37%)` | :arrow_up: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5514/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.71% <0.00%> (+1.50%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5514/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `98.76% <0.00%> (+32.51%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5514/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `94.98% <0.00%> (+74.19%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5514?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5514?src=pr&el=footer). Last update [58cca47...95bbeef](https://codecov.io/gh/huggingface/transformers/pull/5514?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[ { "id": 1314768611, "node_id": "MDU6TGFiZWwxMzE0NzY4NjEx", "url": "https://api.github.com/repos/huggingface/transformers/labels/wontfix", "name": "wontfix", "color": "ffffff", "default": true, "description": null } ]

[]

[ "It seems most of the tests that fail are due to `CUDA error: out of memory`?", "> It seems most of the tests that fail are due to `CUDA error: out of memory`?\r\n\r\nYes. As the message shows, they are due to `CUDA error: out of memory`. \r\nBut I am sure that **no** other processes are using CUDA **before and after** I run the test. \r\nMy machine is with 4 Tesla V100 GPUs. And it works fine with other programs using both single and multi GPUs (e.g. fairseq). \r\nSo I am confused with the error messages. \r\n\r\nBesides, there are some other error messages that show `invalid size` and `INTERNAL ASSERT FAILED`.\r\n\r\nI have tried many environments. All of them fail in `test_multigpu_data_parallel_forward` due to **different** errors which are mainly `out of memory` and `invalid size`. \r\n\r\n", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

[]

[]

[ "@sshleifer Hope you are doing well. sorry for the delay, I have created the PR for some of the related issues which were mentioned in #5057.\r\n> 1. They never use Cuda or fp16, even if they are available.\r\n\r\nI have some doubts which had encountered when making this PR\r\n\r\n---\r\n**1.** As you had said there where some test which failed when enabling the Cuda or fp16\r\n- The Cuda and fp16 are not enabled for question-answering example (`run_squad.py`) as it is having a difference in the f1 score.\r\n- The language-modeling example (`run_language_modeling.py`) is having an issue when running with fp16.\r\n---\r\n**2.** I was not able to find the `test_hans.py` but was able to find a readme to run it. Is this intentional if not shall I have a `test_hans.py` file to run the same.\r\n\r\n\r\n---\r\n**3.** This is the list of tests which I got\r\n```bash\r\n$ ls -l examples/**/test*.py\r\n\r\nexamples/bert-loses-patience/test_run_glue_with_pabee.py\r\nexamples/seq2seq/bertabs/test_utils_summarization.py\r\nexamples/seq2seq/test_seq2seq_examples.py\r\nexamples/test_examples.py\r\nexamples/token-classification/test_ner_examples.py\r\n```\r\nI was not able to find the `test_summarization_examples.py` and `test_t5_examples.py`. I think I am doing something wrong.\r\n\r\n---\r\n**4.** I can have made the PR for some tests only, can do the same for others if the current PR satisfies your requirement. ", "1) noted\r\n2)test_hans.py would be nice, but can be added in a separate PR.\r\n3) You are all set, nothing is wrong. \r\n4) Would love to see the current PR!\r\n\r\nThanks!", "> 2)test_hans.py would be nice, but can be added in a separate PR.\r\n\r\nThe test_hans.py was created once via the PR https://github.com/huggingface/transformers/pull/2239 but I think somehow or for some reason, it was removed\r\n\r\nlast interaction with the file was in the PR https://github.com/huggingface/transformers/pull/4213", "\r\nalso I missed this earlier, but what was the issue with run_language_modeling.py? Can you get a traceback?", "> also I missed this earlier, but what was the issue with run_language_modeling.py? Can you get a traceback?\r\n\r\nThis is the short long and I have attached the pull log with this comment.\r\n```log\r\n with patch.object(sys, \"argv\", testargs):\r\n result = run_language_modeling.main()\r\n> self.assertLess(result[\"perplexity\"], 35)\r\nE AssertionError: 36.684365356893885 not less than 35\r\n```\r\n[test.log](https://github.com/huggingface/transformers/files/4955269/test.log)\r\n", "@sshleifer Hope you are doing well.\r\n\r\nIs this PR ok or Should I split this into multiple smaller PRs to make things easier?", "Thanks for the review @sshleifer, I have updated the code accordingly and regarding the new command line args, I have removed the args which were related to the multi-GPU support as we can make that a separate PR. \r\n\r\n**Any Idea why the test `run_tests_tf` and `run_tests_torch_and_tf` failing? Is it related to my change?**", "Thanks for the review @LysandreJik, I have updated the PR accordingly.", "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5512?src=pr&el=h1) Report\n> Merging [#5512](https://codecov.io/gh/huggingface/transformers/pull/5512?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d9cbc0350deaa7e146a8c8dbb6ad4dc9bd6afc4f?el=desc) will **decrease** coverage by `0.72%`.\n> The diff coverage is `78.87%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5512?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5512 +/- ##\n==========================================\n- Coverage 80.37% 79.64% -0.73% \n==========================================\n Files 156 156 \n Lines 28058 28261 +203 \n==========================================\n- Hits 22552 22509 -43 \n- Misses 5506 5752 +246 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5512?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/commands/serving.py](https://codecov.io/gh/huggingface/transformers/pull/5512/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb21tYW5kcy9zZXJ2aW5nLnB5) | `0.00% <0.00%> (ø)` | |\n| [src/transformers/commands/user.py](https://codecov.io/gh/huggingface/transformers/pull/5512/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb21tYW5kcy91c2VyLnB5) | `0.00% <ø> (ø)` | |\n| [src/transformers/configuration\\_reformer.py](https://codecov.io/gh/huggingface/transformers/pull/5512/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3JlZm9ybWVyLnB5) | `100.00% <ø> (ø)` | |\n| [src/transformers/data/processors/glue.py](https://codecov.io/gh/huggingface/transformers/pull/5512/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvZ2x1ZS5weQ==) | `48.91% <0.00%> (-0.18%)` | :arrow_down: |\n| [src/transformers/data/test\\_generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5512/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Rlc3RfZ2VuZXJhdGlvbl91dGlscy5weQ==) | `0.00% <0.00%> (ø)` | |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5512/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `96.94% <ø> (ø)` | |\n| [src/transformers/hf\\_argparser.py](https://codecov.io/gh/huggingface/transformers/pull/5512/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9oZl9hcmdwYXJzZXIucHk=) | `67.74% <0.00%> (-1.49%)` | :arrow_down: |\n| [src/transformers/modeling\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/5512/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hdXRvLnB5) | `78.73% <ø> (ø)` | |\n| [src/transformers/modeling\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/5512/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19iZXJ0LnB5) | `88.42% <ø> (+0.16%)` | :arrow_up: |\n| [src/transformers/modeling\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5512/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19lbGVjdHJhLnB5) | `82.13% <ø> (ø)` | |\n| ... and [58 more](https://codecov.io/gh/huggingface/transformers/pull/5512/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5512?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5512?src=pr&el=footer). Last update [a573777...51be82f](https://codecov.io/gh/huggingface/transformers/pull/5512?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5511?src=pr&el=h1) Report\n> Merging [#5511](https://codecov.io/gh/huggingface/transformers/pull/5511?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/58cca47c16149e43d1b516623d59e3c5d97f695e&el=desc) will **decrease** coverage by `0.41%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5511?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5511 +/- ##\n==========================================\n- Coverage 77.83% 77.42% -0.42% \n==========================================\n Files 141 141 \n Lines 24634 24634 \n==========================================\n- Hits 19175 19072 -103 \n- Misses 5459 5562 +103 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5511?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/tokenization\\_xlm\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5511/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxtX3JvYmVydGEucHk=) | `61.90% <0.00%> (-33.34%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/5511/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `65.69% <0.00%> (-29.45%)` | :arrow_down: |\n| [src/transformers/tokenization\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/5511/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWFyaWFuLnB5) | `68.14% <0.00%> (-25.67%)` | :arrow_down: |\n| [src/transformers/tokenization\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/5511/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdHJhbnNmb194bC5weQ==) | `33.56% <0.00%> (-8.93%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5511/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `82.99% <0.00%> (-6.13%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5511/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `79.94% <0.00%> (-5.27%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_pytorch\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5511/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9weXRvcmNoX3V0aWxzLnB5) | `88.05% <0.00%> (-1.26%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/5511/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `92.44% <0.00%> (-1.17%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5511/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `98.76% <0.00%> (+32.51%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5511?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5511?src=pr&el=footer). Last update [58cca47...68a7acd](https://codecov.io/gh/huggingface/transformers/pull/5511?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "found out the doc, calling it should work." ]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5510?src=pr&el=h1) Report\n> Merging [#5510](https://codecov.io/gh/huggingface/transformers/pull/5510?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/58cca47c16149e43d1b516623d59e3c5d97f695e&el=desc) will **decrease** coverage by `0.41%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5510?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5510 +/- ##\n==========================================\n- Coverage 77.83% 77.42% -0.41% \n==========================================\n Files 141 141 \n Lines 24634 24634 \n==========================================\n- Hits 19175 19074 -101 \n- Misses 5459 5560 +101 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5510?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5510/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `26.92% <0.00%> (-68.47%)` | :arrow_down: |\n| [src/transformers/tokenization\\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/5510/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYWxiZXJ0LnB5) | `28.84% <0.00%> (-58.66%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5510/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `79.59% <0.00%> (+0.33%)` | :arrow_up: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5510/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.46% <0.00%> (+1.25%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5510/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `98.76% <0.00%> (+32.51%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5510?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5510?src=pr&el=footer). Last update [58cca47...121648f](https://codecov.io/gh/huggingface/transformers/pull/5510?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Thanks a lot!" ]

[ { "id": 1314768611, "node_id": "MDU6TGFiZWwxMzE0NzY4NjEx", "url": "https://api.github.com/repos/huggingface/transformers/labels/wontfix", "name": "wontfix", "color": "ffffff", "default": true, "description": null } ]

[]

[ "Hi @misrasaurabh1 I have also faced this issue. One immediate solution is to use lazy loading dataset, as xla by default loads the dataset in all processes. Something like `nlp` can really help here. as posted by @thomwolf here https://gist.github.com/thomwolf/13ca2b2b172b2d17ac66685aa2eeba62\r\n\r\n`nlp` can load full english wikipedia dataset (17 GB+) in just 9 MB of RAM. However I've not been able to use it with TPU's yet.", "Very interesting, if one could load data in a lazy-loading manner using `nlp` it would help a lot! Although I am not sure if we can use our custom datasets with `nlp`.\r\n\r\nIf there was a way to use a shared memory between different processes or each process reading independently from memory-mapped on drive, that could solve this problem.", "It's possible to use custom datasets with `nlp`. This section can help you https://github.com/huggingface/nlp/blob/master/CONTRIBUTING.md#how-to-add-a-dataset\r\n\r\nWe can create dataset as described in above steps, and then just pass the path of created dataset to `nlp.load_dataset` ", "Although I still want to highlight that this bug is still unfixed and a big problem. Drawing attention from the HuggingFace team!", "Update on how I solved the large memory usage. Because I just wanted one copy of the features in memory, so I used a redis-server locally to cache the features in memory in a separate process. I am also using unix sockets to make connections faster. Items stored in Redis have keys equal to the array index and value equal to the pickled feature dictionary. In the __getitem__ I am unpickling the data on the fly.\r\nThis reduced memory consumption from 100s of GBs to 30GB. Surprisingly, the training also became 20% faster after using redis-server.", "Thanks for sharing this @misrasaurabh1 ", "Thanks for letting us know @misrasaurabh1! We're very close to having TPU CI, only a few days away to a week, so we'll be able to monitor such metrics more closely.", "Although the memory still keeps increasing as the training progresses. If it becomes too much of an issue for a reliable training pipeline I can dig deeper.", "The memory spikes up everytime evaluation loop happens.\r\n\r\n", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

[]

[]

[ "`min_length` corresponds to the minimum number of tokens, not words.\r\n\r\nFeel free to reopen if this does not answer your question." ]

[ { "id": 1834056635, "node_id": "MDU6TGFiZWwxODM0MDU2NjM1", "url": "https://api.github.com/repos/huggingface/transformers/labels/Core:%20Tokenization", "name": "Core: Tokenization", "color": "FF4446", "default": false, "description": "Internals of the library; Tokenization." } ]

[]

[ "Thanks for flagging, the docstrings were indeed very confusing!\r\nI hope the new doc introduced in #5559 is clearer and solves your problem. Please reopen if needed.", "Thanks for the clarification in the new doc! Does it mean RoBERTa was pre-trained **without** this add_prefix_space behavior? In other words, in the original model, does it encode \"Hello world\" with 2 or 3 tokens, excluding special tokens? If it was pre-trained without adding the prefix space, does it mean the **fast tokenizers** in the pre-3.0.0 transformers versions were adding this prefix space incorrectly?", "E.g. in 2.11.0\r\n```\r\n>>> from transformers import RobertaTokenizerFast\r\n>>> tokenizer = RobertaTokenizerFast.from_pretrained(\"roberta-base\")\r\n>>> tokenizer.tokenize(\"Hello world\")\r\n['ĠHello', 'Ġworld']\r\n```", "I think it was incorrect, yes, since it currently returns `['Hello', 'Ġworld']` like the slow tokenizer. Multiple bugs in fast tokenizer were fixed in 3.0.0." ]

[]

[]

[ "The `encoder_attention_mask` is only relevant if BERT is uses as a Encoder-Decoder model using the `EncoderDecoderModel` wrapper class. In this case the decoder should be able to accept an `encoder_attention_mask` for its cross-attention layers. \r\n\r\nIn all other cases this mask is not relevant and should be set to None. \r\n\r\nI agree that the check `if self.is_decoder` is probably not the best one here it should rather be `if self.is_encoder_decoder and self.is_decoder`. will update this soon.\r\n\r\nFeel free to reopen if this does not answer your question", "Hi Patrick, thanks for the swift response. I’m not sure if I understand: shouldn’t we always want to mask the padded tokens, even in the encoder?\r\n\r\nIn fact the canonical BERT model suggests this, where they have no such check: https://github.com/google-research/bert/blob/master/modeling.py#L200", "@patrickvonplaten Sorry for the noise. Noticed you said to reopen the issue but I think only maintainers have this permission :)", "This `encoder_attention_mask` is only relevent for a Bert EncoderDecoder model. It is not the same as the usual `attention_mask`", "Ah, I see. Looking again at the code I definitely misunderstood that. Thanks a ton." ]

[]

[]

[ "same problem here", "same problem here", "I bumped the same problem. After a plenty of warning messages my colab stuck and web-page didn't answer. As a temporary solution I installed previous version of transformers library ```!pip install transformers==3.0.0``` and evething with ```BertTokenizer.batch_encode_plus()``` is okay.", "The massive amount of generated warnings is crashing the Google Colab session in my Chrome browser. The only temporary fix I can find is to turn off all warning messages.\r\n\r\n```python\r\nimport logging\r\nlogging.basicConfig(level=logging.ERROR)\r\n```", "same even when the `batch_encode_plus` method is not called (directly calling `tokenizer()` with a list of string)", "Ok indeed, we are on it and will release a fix soon. Sorry for that.", "Tested in 3.0.2 - warning persists.", "Can you post the command line (tokenizer call) you are running?", "Same here, have tried myriad combinations to try to eliminate the warning.\r\n\r\n```\r\nmodel = Seq2SeqModel(\r\n encoder_type,\r\n \"roberta-base\",\r\n \"bert-base-cased\",\r\n args=model_args,\r\n truncation=True,\r\n use_cuda=cuda_available\r\n)\r\n```\r\n\r\n> WARNING:transformers.tokenization_utils_base:Truncation was not explicitely activated but `max_length` is provided a specific value, please use `truncation=True` to explicitely truncate examples to max length. Defaulting to 'longest_first' truncation strategy. If you encode pairs of sequences (GLUE-style) with the tokenizer you can select this strategy more precisely by providing a specific strategy to `truncation`.\r\n> WARNING:transformers.tokenization_utils_base:Truncation was not explicitely activated but `max_length` is provided a specific value, please use `truncation=True` to explicitely truncate examples to max length. Defaulting to 'longest_first' truncation strategy. If you encode pairs of sequences (GLUE-style) with the tokenizer you can select this strategy more precisely by providing a specific strategy to `truncation`.\r\n> WARNING:transformers.tokenization_utils_base:Truncation was not explicitely activated but `max_length` is provided a specific value, please use `truncation=True` to explicitely truncate examples to max length. Defaulting to 'longest_first' truncation strategy. If you encode pairs of sequences (GLUE-style) with the tokenizer you can select this strategy more precisely by providing a specific strategy to `truncation`.\r\n> WARNING:transformers.tokenization_utils_base:Truncation was not explicitely activated but `max_length` is provided a specific value, please use `truncation=True` to explicitely truncate examples to max length. Defaulting to 'longest_first' truncation strategy. If you encode pairs of sequences (GLUE-style) with the tokenizer you can select this strategy more precisely by providing a specific strategy to `truncation`.\r\n", "I can't find the class `Seq2SeqModel` on our repo so I can't reproduce your code.\r\n\r\nYou need to open a new issue with all the details so I can try to reproduce and debug this.", "Should only print it once" ]

[ { "id": 1314768611, "node_id": "MDU6TGFiZWwxMzE0NzY4NjEx", "url": "https://api.github.com/repos/huggingface/transformers/labels/wontfix", "name": "wontfix", "color": "ffffff", "default": true, "description": null } ]

[]

[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

[ { "id": 1314768611, "node_id": "MDU6TGFiZWwxMzE0NzY4NjEx", "url": "https://api.github.com/repos/huggingface/transformers/labels/wontfix", "name": "wontfix", "color": "ffffff", "default": true, "description": null } ]

[]

[ "Hi @santhoshkolloju what is the xla and pytorch version ?", "Pytorch - 1.7.0a0+542ac74\r\ntorch_xla - 1.6+30b65e9\r\nThe setup file is taken from \r\nVERSION = \"nightly\" #@param [\"1.5\" , \"20200325\", \"nightly\"]\r\n!curl https://raw.githubusercontent.com/pytorch/xla/master/contrib/scripts/env-setup.py -o pytorch-xla-env-setup.py\r\n!python pytorch-xla-env-setup.py --version $VERSION", "@patil-suraj i just realised that i was using the notebook created by you. Thanks for the notebook.\r\nDid anything has changed in the current xla library because of which this is happening? ", "Hi @santhoshkolloju , yes there's been some changes to xla, I'm working on the fix, will let you know when I find it.\r\n\r\nAlso looks like you are trying to do question generation, I am going to release my own experiments by the end of the week. It's pretty exciting. Here's a relevant thread for QG #4399", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

[]

[]

[]

[]

[]

[]

[ { "id": 1834056635, "node_id": "MDU6TGFiZWwxODM0MDU2NjM1", "url": "https://api.github.com/repos/huggingface/transformers/labels/Core:%20Tokenization", "name": "Core: Tokenization", "color": "FF4446", "default": false, "description": "Internals of the library; Tokenization." } ]

[]

[ "Indeed, if you are using padding you need to provide the attention masks to your model otherwise it doesn't know which tokens it should not attend to.\r\n\r\nHere is the correct version of `batch_encoding` which will give the same output as the non batched version:\r\n```python\r\ndef batch_encoding(sentences):\r\n \r\n inputs = tokenizer(sentences, padding=True, return_tensors='pt')\r\n print(inputs)\r\n outputs = model(**inputs)\r\n features = outputs[0][:,0,:].detach().numpy()\r\n \r\n return features\r\n```\r\nI've also updated it to the new tokenizers API on which you can learn a lot more in the tutorial here: https://huggingface.co/transformers/preprocessing.html", "@thomwolf I am using the pre-trained distilbert model.\r\nencoded_batch = tokenizer.batch_encode_plus([\"hello\", \"there you\"], add_special_tokens=True, return_tensors=\"tf\", padding=True, truncation=True)\r\n`{'input_ids': <tf.Tensor: shape=(2, 4), dtype=int32, numpy=\r\narray([[ 101, 7592, 102, 0],\r\n [ 101, 2045, 2017, 102]], dtype=int32)>, 'attention_mask': <tf.Tensor: shape=(2, 4), dtype=int32, numpy=\r\narray([[1, 1, 1, 0],\r\n [1, 1, 1, 1]], dtype=int32)>}`\r\n\r\nencoded_batch[0][0] -> pointing to hidden states of \"hello\"\r\n<tf.Tensor: shape=(4, 768), dtype=float32, numpy=\r\narray([[-0.20557329, -0.18245512, 0.0950693 , ..., -0.06398913,\r\n 0.16745588, 0.37530535],\r\n [-0.48316494, -0.13651992, 0.3210112 , ..., 0.0130196 ,\r\n 0.27123356, 0.15390822],\r\n [ 0.8976611 , 0.14261621, -0.40148023, ..., 0.31185225,\r\n -0.68173647, -0.2594604 ],\r\n [-0.0716978 , -0.18830499, 0.35636497, ..., 0.09993267,\r\n -0.05575091, 0.14572877]], dtype=float32)>\r\n\r\n\r\nand if i encode \"hello\" alone, \r\n<tf.Tensor: shape=(3, 768), dtype=float32, numpy=\r\narray([[-0.20557335, -0.18245521, 0.09506968, ..., -0.06398894,\r\n 0.16745585, 0.37530527],\r\n [-0.48316532, -0.13651986, 0.32101193, ..., 0.0130194 ,\r\n 0.27123365, 0.15390885],\r\n [ 0.89766103, 0.14261642, -0.40148014, ..., 0.31185254,\r\n -0.68173563, -0.25946063]], dtype=float32)>\r\n\r\nso here, if you see, \r\nthere is one row extra due to padding in the above instance,\r\nand there is no way to figure out if that is SEP embeds or padded embeds\r\nand that can lead to discrepancies.\r\n\r\nIs there some way to send inputs to the model in a batch, keeping the embeddings intact?\r\n\r\n\r\nThanks in advance" ]

[ { "id": 1314768611, "node_id": "MDU6TGFiZWwxMzE0NzY4NjEx", "url": "https://api.github.com/repos/huggingface/transformers/labels/wontfix", "name": "wontfix", "color": "ffffff", "default": true, "description": null } ]

[]

[ "Hi, can you provide more information (basically fill all the filed in the issue templates) in particular provide a clear example so we can try to reproduce the behavior?", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

[]

[ { "login": "joeddav", "id": 9353833, "node_id": "MDQ6VXNlcjkzNTM4MzM=", "avatar_url": "https://avatars.githubusercontent.com/u/9353833?v=4", "gravatar_id": "", "url": "https://api.github.com/users/joeddav", "html_url": "https://github.com/joeddav", "followers_url": "https://api.github.com/users/joeddav/followers", "following_url": "https://api.github.com/users/joeddav/following{/other_user}", "gists_url": "https://api.github.com/users/joeddav/gists{/gist_id}", "starred_url": "https://api.github.com/users/joeddav/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/joeddav/subscriptions", "organizations_url": "https://api.github.com/users/joeddav/orgs", "repos_url": "https://api.github.com/users/joeddav/repos", "events_url": "https://api.github.com/users/joeddav/events{/privacy}", "received_events_url": "https://api.github.com/users/joeddav/received_events", "type": "User", "site_admin": false } ]

[ "We're back up, and should now be setup to auto-restart when it fails. Thanks for the heads up!", "Awsome! Thanks.", "Hi! It seems the page is down again.", "Man, streamlit's killing me. Thanks, rebooting now.", "Ouch, this means we users are indirectly killing you! Thanks a lot. 🙂 ", "This page is giving me a 502. reopen this issue, please", "Back up, and fixed the issue with auto-relaunch. Thanks for the heads up.", "Hi! Thanks for the great demo!\r\nThe page seems to be down again.", "This time it was actually just me making some changes. Back up.", "I am getting a timeout on it... so, still not available I think..." ]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5497?src=pr&el=h1) Report\n> Merging [#5497](https://codecov.io/gh/huggingface/transformers/pull/5497?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/49281ac9390e19f30c30a914b11aa55b561973d1&el=desc) will **decrease** coverage by `0.23%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5497?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5497 +/- ##\n==========================================\n- Coverage 77.82% 77.59% -0.24% \n==========================================\n Files 141 141 \n Lines 24617 24619 +2 \n==========================================\n- Hits 19159 19103 -56 \n- Misses 5458 5516 +58 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5497?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5497/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `84.71% <100.00%> (-1.47%)` | :arrow_down: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5497/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `96.82% <100.00%> (+<0.01%)` | :arrow_up: |\n| [src/transformers/tokenization\\_xlm\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5497/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxtX3JvYmVydGEucHk=) | `61.90% <0.00%> (-33.34%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/5497/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `65.69% <0.00%> (-29.45%)` | :arrow_down: |\n| [src/transformers/tokenization\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/5497/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdHJhbnNmb194bC5weQ==) | `33.56% <0.00%> (-8.93%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5497/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `84.01% <0.00%> (-5.11%)` | :arrow_down: |\n| [src/transformers/tokenization\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/5497/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYXV0by5weQ==) | `95.55% <0.00%> (-2.23%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/5497/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `92.89% <0.00%> (-1.33%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_pytorch\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5497/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9weXRvcmNoX3V0aWxzLnB5) | `88.05% <0.00%> (-1.26%)` | :arrow_down: |\n| ... and [2 more](https://codecov.io/gh/huggingface/transformers/pull/5497/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5497?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5497?src=pr&el=footer). Last update [49281ac...3e5929c](https://codecov.io/gh/huggingface/transformers/pull/5497?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Should be trivial to merge this IMO. Is there any case why one would now receive an error if `max_length` < `cur_len` @sshleifer @yjernite ?", "Is max_length still meant to include the length of input_ids?", "yes! Would you change it to be added to the input?", "I don't understand your response exactly. My preference is that `max_length` is completely independent of the ids sent to the encoder. That is how the current code works. For example, if we are summarizing a news article of length `X`, and max_length is 20, we should be allowed to generate 20 tokens regardless of `X`. \r\nFor the text generation use case, I care less, but I have the same opinion. `X.shape[1]` should not matter.\r\nI don't have an opinion on whether `decoder_start_token_id` counts.\r\nWhen does this assert get hit?", "The assert hits at the moment only for text-generation of \"encoder\" only models (GPT2, XLNET, ...) if `input_ids.shape[1] >= max_length`. \r\nIn the case of all \"conditional\" generation (using an encoder + decoder, like Bart / T5) `max_length` is independent of the input to the encoder because auto-regressive generation is only done for the decoder => which is expected.\r\n\r\nThe question is whether for text generation of encoder only models like gpt2 `max_length` should be changed to something like `max_tokens_to_generate` in which case the limit would be `input_ids.shape[1] + max_tokens_to_generate` (independent of `input_ids`). Not sure whether it's more intuitive to define the number of max length tokens **to be generated** or better the max length of the complete text, also given the name `max_length`. ", "I think `max_length` should refer to the maximum number of tokens that can be generated.\r\nFor example, if you wanted to make a next word suggester, it would be much simpler to have max_length=1, than it would be check how many input_ids != pad_token_id for each entry in your batch and then add 1 to that.\r\n\r\nI don't think there are as many use cases where you need N tokens regardless of the length of the input. " ]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5496?src=pr&el=h1) Report\n> Merging [#5496](https://codecov.io/gh/huggingface/transformers/pull/5496?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/21cd8c40862ba356096ab4cda31563ee3a35c1bb&el=desc) will **increase** coverage by `1.14%`.\n> The diff coverage is `85.71%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5496?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5496 +/- ##\n==========================================\n+ Coverage 76.39% 77.54% +1.14% \n==========================================\n Files 141 141 \n Lines 24617 24622 +5 \n==========================================\n+ Hits 18807 19092 +285 \n+ Misses 5810 5530 -280 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5496?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/5496/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `28.34% <50.00%> (+0.13%)` | :arrow_up: |\n| [src/transformers/pipelines.py](https://codecov.io/gh/huggingface/transformers/pull/5496/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9waXBlbGluZXMucHk=) | `76.12% <100.00%> (+0.12%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5496/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `20.78% <0.00%> (-74.20%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/5496/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `65.69% <0.00%> (-29.45%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5496/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `84.01% <0.00%> (-5.11%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5496/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `79.72% <0.00%> (-1.38%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_pytorch\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5496/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9weXRvcmNoX3V0aWxzLnB5) | `88.05% <0.00%> (-1.26%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5496/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `85.92% <0.00%> (-0.51%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5496/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `95.38% <0.00%> (+68.46%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/5496/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `96.72% <0.00%> (+73.10%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5496?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5496?src=pr&el=footer). Last update [21cd8c4...b716a86](https://codecov.io/gh/huggingface/transformers/pull/5496?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5495?src=pr&el=h1) Report\n> Merging [#5495](https://codecov.io/gh/huggingface/transformers/pull/5495?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/8438bab38e1ea60efca181c92ebc7e4602f91848&el=desc) will **increase** coverage by `0.76%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5495?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5495 +/- ##\n==========================================\n+ Coverage 76.97% 77.74% +0.76% \n==========================================\n Files 141 141 \n Lines 24617 24617 \n==========================================\n+ Hits 18950 19138 +188 \n+ Misses 5667 5479 -188 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5495?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/tokenization\\_t5.py](https://codecov.io/gh/huggingface/transformers/pull/5495/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdDUucHk=) | `71.83% <0.00%> (-23.95%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5495/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `83.41% <0.00%> (-2.27%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/5495/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `94.21% <0.00%> (+1.32%)` | :arrow_up: |\n| [src/transformers/tokenization\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/5495/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdHJhbnNmb194bC5weQ==) | `42.48% <0.00%> (+8.92%)` | :arrow_up: |\n| [src/transformers/tokenization\\_xlm.py](https://codecov.io/gh/huggingface/transformers/pull/5495/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxtLnB5) | `82.93% <0.00%> (+66.66%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5495?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5495?src=pr&el=footer). Last update [8438bab...74a8457](https://codecov.io/gh/huggingface/transformers/pull/5495?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Thanks for the fix!" ]

[]

[]

[ "Turning off the eager mode of tensorflow makes inference much faster." ]

[ { "id": 1838412367, "node_id": "MDU6TGFiZWwxODM4NDEyMzY3", "url": "https://api.github.com/repos/huggingface/transformers/labels/model%20card", "name": "model card", "color": "92d5f4", "default": false, "description": "Related to pretrained model cards" } ]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5493?src=pr&el=h1) Report\n> Merging [#5493](https://codecov.io/gh/huggingface/transformers/pull/5493?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/21cd8c40862ba356096ab4cda31563ee3a35c1bb&el=desc) will **increase** coverage by `1.82%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5493?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5493 +/- ##\n==========================================\n+ Coverage 76.39% 78.22% +1.82% \n==========================================\n Files 141 141 \n Lines 24617 24617 \n==========================================\n+ Hits 18807 19257 +450 \n+ Misses 5810 5360 -450 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5493?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5493/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9yb2JlcnRhLnB5) | `43.47% <0.00%> (-49.57%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5493/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `66.25% <0.00%> (-32.52%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5493/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHMucHk=) | `90.22% <0.00%> (+0.31%)` | :arrow_up: |\n| [src/transformers/tokenization\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5493/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fb3BlbmFpLnB5) | `83.84% <0.00%> (+1.53%)` | :arrow_up: |\n| [src/transformers/tokenization\\_utils\\_fast.py](https://codecov.io/gh/huggingface/transformers/pull/5493/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfZmFzdC5weQ==) | `94.20% <0.00%> (+2.17%)` | :arrow_up: |\n| [src/transformers/tokenization\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/5493/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmVydC5weQ==) | `89.95% <0.00%> (+2.28%)` | :arrow_up: |\n| [src/transformers/tokenization\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/5493/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdHJhbnNmb194bC5weQ==) | `42.48% <0.00%> (+3.75%)` | :arrow_up: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/5493/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `94.21% <0.00%> (+8.92%)` | :arrow_up: |\n| [src/transformers/tokenization\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5493/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fcm9iZXJ0YS5weQ==) | `94.52% <0.00%> (+17.80%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5493/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `95.38% <0.00%> (+68.46%)` | :arrow_up: |\n| ... and [1 more](https://codecov.io/gh/huggingface/transformers/pull/5493/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5493?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5493?src=pr&el=footer). Last update [21cd8c4...5e82926](https://codecov.io/gh/huggingface/transformers/pull/5493?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[ { "id": 1838412367, "node_id": "MDU6TGFiZWwxODM4NDEyMzY3", "url": "https://api.github.com/repos/huggingface/transformers/labels/model%20card", "name": "model card", "color": "92d5f4", "default": false, "description": "Related to pretrained model cards" } ]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5492?src=pr&el=h1) Report\n> Merging [#5492](https://codecov.io/gh/huggingface/transformers/pull/5492?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/21cd8c40862ba356096ab4cda31563ee3a35c1bb&el=desc) will **increase** coverage by `1.82%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5492?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5492 +/- ##\n==========================================\n+ Coverage 76.39% 78.22% +1.82% \n==========================================\n Files 141 141 \n Lines 24617 24617 \n==========================================\n+ Hits 18807 19257 +450 \n+ Misses 5810 5360 -450 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5492?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5492/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9yb2JlcnRhLnB5) | `43.47% <0.00%> (-49.57%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5492/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `66.25% <0.00%> (-32.52%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5492/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHMucHk=) | `90.22% <0.00%> (+0.31%)` | :arrow_up: |\n| [src/transformers/tokenization\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5492/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fb3BlbmFpLnB5) | `83.84% <0.00%> (+1.53%)` | :arrow_up: |\n| [src/transformers/tokenization\\_utils\\_fast.py](https://codecov.io/gh/huggingface/transformers/pull/5492/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfZmFzdC5weQ==) | `94.20% <0.00%> (+2.17%)` | :arrow_up: |\n| [src/transformers/tokenization\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/5492/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmVydC5weQ==) | `89.95% <0.00%> (+2.28%)` | :arrow_up: |\n| [src/transformers/tokenization\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/5492/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdHJhbnNmb194bC5weQ==) | `42.48% <0.00%> (+3.75%)` | :arrow_up: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/5492/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `94.21% <0.00%> (+8.92%)` | :arrow_up: |\n| [src/transformers/tokenization\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5492/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fcm9iZXJ0YS5weQ==) | `94.52% <0.00%> (+17.80%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5492/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `95.38% <0.00%> (+68.46%)` | :arrow_up: |\n| ... and [1 more](https://codecov.io/gh/huggingface/transformers/pull/5492/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5492?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5492?src=pr&el=footer). Last update [21cd8c4...31db433](https://codecov.io/gh/huggingface/transformers/pull/5492?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[ { "id": 1838412367, "node_id": "MDU6TGFiZWwxODM4NDEyMzY3", "url": "https://api.github.com/repos/huggingface/transformers/labels/model%20card", "name": "model card", "color": "92d5f4", "default": false, "description": "Related to pretrained model cards" } ]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5491?src=pr&el=h1) Report\n> Merging [#5491](https://codecov.io/gh/huggingface/transformers/pull/5491?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/21cd8c40862ba356096ab4cda31563ee3a35c1bb&el=desc) will **increase** coverage by `1.82%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5491?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5491 +/- ##\n==========================================\n+ Coverage 76.39% 78.22% +1.82% \n==========================================\n Files 141 141 \n Lines 24617 24617 \n==========================================\n+ Hits 18807 19257 +450 \n+ Misses 5810 5360 -450 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5491?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5491/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9yb2JlcnRhLnB5) | `43.47% <0.00%> (-49.57%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5491/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `66.25% <0.00%> (-32.52%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5491/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHMucHk=) | `90.22% <0.00%> (+0.31%)` | :arrow_up: |\n| [src/transformers/tokenization\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5491/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fb3BlbmFpLnB5) | `83.84% <0.00%> (+1.53%)` | :arrow_up: |\n| [src/transformers/tokenization\\_utils\\_fast.py](https://codecov.io/gh/huggingface/transformers/pull/5491/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfZmFzdC5weQ==) | `94.20% <0.00%> (+2.17%)` | :arrow_up: |\n| [src/transformers/tokenization\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/5491/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmVydC5weQ==) | `89.95% <0.00%> (+2.28%)` | :arrow_up: |\n| [src/transformers/tokenization\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/5491/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdHJhbnNmb194bC5weQ==) | `42.48% <0.00%> (+3.75%)` | :arrow_up: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/5491/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `94.21% <0.00%> (+8.92%)` | :arrow_up: |\n| [src/transformers/tokenization\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5491/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fcm9iZXJ0YS5weQ==) | `94.52% <0.00%> (+17.80%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5491/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `95.38% <0.00%> (+68.46%)` | :arrow_up: |\n| ... and [1 more](https://codecov.io/gh/huggingface/transformers/pull/5491/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5491?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5491?src=pr&el=footer). Last update [21cd8c4...cf45716](https://codecov.io/gh/huggingface/transformers/pull/5491?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[ { "id": 1834056635, "node_id": "MDU6TGFiZWwxODM0MDU2NjM1", "url": "https://api.github.com/repos/huggingface/transformers/labels/Core:%20Tokenization", "name": "Core: Tokenization", "color": "FF4446", "default": false, "description": "Internals of the library; Tokenization." } ]

[ { "login": "n1t0", "id": 1217986, "node_id": "MDQ6VXNlcjEyMTc5ODY=", "avatar_url": "https://avatars.githubusercontent.com/u/1217986?v=4", "gravatar_id": "", "url": "https://api.github.com/users/n1t0", "html_url": "https://github.com/n1t0", "followers_url": "https://api.github.com/users/n1t0/followers", "following_url": "https://api.github.com/users/n1t0/following{/other_user}", "gists_url": "https://api.github.com/users/n1t0/gists{/gist_id}", "starred_url": "https://api.github.com/users/n1t0/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/n1t0/subscriptions", "organizations_url": "https://api.github.com/users/n1t0/orgs", "repos_url": "https://api.github.com/users/n1t0/repos", "events_url": "https://api.github.com/users/n1t0/events{/privacy}", "received_events_url": "https://api.github.com/users/n1t0/received_events", "type": "User", "site_admin": false } ]

[ "This is related to https://github.com/huggingface/transformers/issues/2917. In the slow tokenizers, when `do_lower_case=False` we don't strip accents, while we do it when `do_lower_case=True`. In the fast tokenizers, this is controlled by the `strip_accents` option, which is `True` here.\r\n\r\n@thomwolf How do you think we should fix this?", "Yes let's do it @n1t0 and stick to the official bert tokenizer behavior in the fast tokenizers as well." ]

[]

[ { "login": "patrickvonplaten", "id": 23423619, "node_id": "MDQ6VXNlcjIzNDIzNjE5", "avatar_url": "https://avatars.githubusercontent.com/u/23423619?v=4", "gravatar_id": "", "url": "https://api.github.com/users/patrickvonplaten", "html_url": "https://github.com/patrickvonplaten", "followers_url": "https://api.github.com/users/patrickvonplaten/followers", "following_url": "https://api.github.com/users/patrickvonplaten/following{/other_user}", "gists_url": "https://api.github.com/users/patrickvonplaten/gists{/gist_id}", "starred_url": "https://api.github.com/users/patrickvonplaten/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/patrickvonplaten/subscriptions", "organizations_url": "https://api.github.com/users/patrickvonplaten/orgs", "repos_url": "https://api.github.com/users/patrickvonplaten/repos", "events_url": "https://api.github.com/users/patrickvonplaten/events{/privacy}", "received_events_url": "https://api.github.com/users/patrickvonplaten/received_events", "type": "User", "site_admin": false } ]

[ "Hmm, this will be hard to debug here. I'm currently working on getting a working example of a Bert2Bert model, so I will keep an eye on `encoder_output` bugs!\r\nSee conversation here: https://github.com/huggingface/transformers/issues/4443#issuecomment-656691026", "Thank you for your reply.\r\nI am looking forward your Bert2Bert example. And I hope we can solve this problem.", "Hey @bobshih, \r\n\r\nTraining a Bert2Bert model worked out fine for me - I did not experience any bugs related to `encoder_outputs`. \r\nYou can check out the model and all the code to reproduce the results here:\r\nhttps://huggingface.co/patrickvonplaten/bert2bert-cnn_dailymail-fp16\r\n\r\nMaybe you can take a look, adapt your code and see whether the error persists :-) ", "OK, thank for your attention.\r\nI will adapt my code after finishing my work at hand.\r\n", "Hi, @patrickvonplaten,\r\nI have trained EncoderDecoderModel with your training example script.\r\nI noticed that if there are too many padding tokens in training data, it will make the trained model produce the same vectors despite the different inputs.\r\nbut I wonder why attention mask does not work?\r\nIn my original training setting, there are 93% padding tokens. After I reduce the max length and make padding tokens decrease to 21%, the encoderdecoder model works without problems.", "This line:\r\n\r\nhttps://huggingface.co/patrickvonplaten/bert2bert-cnn_dailymail-fp16#training-script:\r\n\r\n```python\r\n batch[\"labels\"] = [\r\n [-100 if token == tokenizer.pad_token_id else token for token in labels] for labels in batch[\"labels\"]\r\n ]\r\n```\r\n\r\nin the preprocessing should make sure that the PAD token does not influence the loss and thus also not the model.", "> This line:\r\n> \r\n> https://huggingface.co/patrickvonplaten/bert2bert-cnn_dailymail-fp16#training-script:\r\n> \r\n> ```python\r\n> batch[\"labels\"] = [\r\n> [-100 if token == tokenizer.pad_token_id else token for token in labels] for labels in batch[\"labels\"]\r\n> ]\r\n> ```\r\n> \r\n> in the preprocessing should make sure that the PAD token does not influence the loss and thus also not the model.\r\n\r\nYes, I understand what you mention, and I also use this setting for models after adapting my script, but the problem shows again.\r\nI will train the model again with this setting in the weekend. And I hope there will be a different result.\r\nAgain, thank you very much for solving the problem and patience." ]

[]

[]

[ "I figured out the issue. I should not set `--local_rank=$SLURM_LOCALID` in the argument. `torch.distributed.launch` will automatically pass the right --local_rank value to run_language_modeling.py. " ]

[ { "id": 1314768611, "node_id": "MDU6TGFiZWwxMzE0NzY4NjEx", "url": "https://api.github.com/repos/huggingface/transformers/labels/wontfix", "name": "wontfix", "color": "ffffff", "default": true, "description": null } ]

[]

[ "I agree with this request. TPU training pipeline is very fragile, lacking and needs more attention. Encouraging more use of TPU by providing easy examples would increase its usage resulting in a higher quality TPU Training system over time as more people contribute.", "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

[ { "id": 1834056635, "node_id": "MDU6TGFiZWwxODM0MDU2NjM1", "url": "https://api.github.com/repos/huggingface/transformers/labels/Core:%20Tokenization", "name": "Core: Tokenization", "color": "FF4446", "default": false, "description": "Internals of the library; Tokenization." } ]

[ { "login": "n1t0", "id": 1217986, "node_id": "MDQ6VXNlcjEyMTc5ODY=", "avatar_url": "https://avatars.githubusercontent.com/u/1217986?v=4", "gravatar_id": "", "url": "https://api.github.com/users/n1t0", "html_url": "https://github.com/n1t0", "followers_url": "https://api.github.com/users/n1t0/followers", "following_url": "https://api.github.com/users/n1t0/following{/other_user}", "gists_url": "https://api.github.com/users/n1t0/gists{/gist_id}", "starred_url": "https://api.github.com/users/n1t0/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/n1t0/subscriptions", "organizations_url": "https://api.github.com/users/n1t0/orgs", "repos_url": "https://api.github.com/users/n1t0/repos", "events_url": "https://api.github.com/users/n1t0/events{/privacy}", "received_events_url": "https://api.github.com/users/n1t0/received_events", "type": "User", "site_admin": false } ]

[ "This might help you: https://stackoverflow.com/questions/62691279/how-to-disable-tokenizers-parallelism-true-false-warning", "I suspect this may be caused by loading data. In my case, it happens when my dataloader starts working.", "This is happening whenever you use `multiprocessing` (Often used by data loaders). The way to disable this warning is to set the `TOKENIZERS_PARALLELISM` environment variable to the value that makes more sense for you. By default, we disable the parallelism to avoid any hidden deadlock that would be hard to debug, but you might be totally fine while keeping it enabled in your specific use-case.\r\n\r\nYou can try to set it to `true`, and if your process seems to be stuck, doing nothing, then you should use `false`.\r\n\r\nWe'll improve this message to help avoid any confusion (Cf https://github.com/huggingface/tokenizers/issues/328)", "I may be a rookie, but it seems like it would be useful to indicate that this is an environment variable in the warning message.", "You are totally right! In the latest version `3.0.2`, the warning message should be a lot better, and it will trigger only when necessary.", "Hi, sorry to bump this thread... \r\n\r\nI'm having the same problem however, the tokenizer is used only in my model. \r\n\r\nData loading is made with multiple workers but it is only loading raw text which is then given to the model and only the model uses the tokenizer. \r\nI don't have multi model or whatever, just a classic pytorch model. \r\n\r\nThus I was wondering how can I have the warning. \r\n\r\nThanks in advance, \r\nHave a great day :) ", "You must be using a tokenizer before using `multiprocessing`. When your process gets forked, you see this message because it detects that a fork is happening and that some kind of parallelism was used before.", "@n1t0, \r\nThanks a lot for the fast reply, \r\nI guess it detect a fork even if it's safe for me to do so... Yes my process is forked but not the tokenizer. \r\n\r\nThen I will use the env variable to remove the warning. ", "I use ```tokenizer``` in my data loader.\r\n\r\nIf that is the source of this problem (hence disabling the parallelization --> hence slow training), then what is the solution? \r\n\r\nUsing ```tokenizer``` in the pre-processing step? ", "After testing, it is found that when the data in a dataloader is processed by the token, and the datalodaer jumps out before it is finished, this warning will be triggered; \r\nI give a code example:\r\n```\r\n# for example, following code will trigger the warning\r\nfor texts in train_dataloader:\r\n _ = tokenizer.batch_encode_plus(texts)\r\n # loader has not been traversed\r\n # but texts are used\r\n break \r\nfor texts in test_dataloader:\r\n # warning ...\r\n pass or break\r\n\r\n# and following code will not trigger the warning\r\nfor texts in train_dataloader:\r\n # loader has not been traversed\r\n # but texts are not used\r\n break \r\nfor texts in test_dataloader:\r\n # No warning \r\n pass or break\r\n```", "@hbchen121 my dataloader processes the text in init function\r\n\r\nDuring data loading time, directly input_ids and attention masks are fetched, yet I get this warning.", "Despite [the documentation](https://huggingface.co/transformers/v3.0.2/model_doc/auto.html) saying that `use_fast` defaults to `False`, adding `use_fast=False` so that it's `AutoTokenizer.from_pretrained(model_name, use_fast=False)` removed this warning for me. If I just use `AutoTokenizer.from_pretrained(model_name)`, the warning pops up again.", "I want to know if we can ignore this warning. What bad effects will it have? Will it affect the training results? Or is it just a little slower? If the environment variables are changed according to the above solution, what is the cost of doing so?", "cc @ArthurZucker", "> I want to know if we can ignore this warning. What bad effects will it have? Will it affect the training results? Or is it just a little slower? If the environment variables are changed according to the above solution, what is the cost of doing so?\r\n\r\n@hzphzp there is an explanation in SO\r\nhttps://stackoverflow.com/questions/62691279/how-to-disable-tokenizers-parallelism-true-false-warning/72926996#72926996", "> > I want to know if we can ignore this warning. What bad effects will it have? Will it affect the training results? Or is it just a little slower? If the environment variables are changed according to the above solution, what is the cost of doing so?\r\n> \r\n> @hzphzp there is an explanation in SO https://stackoverflow.com/questions/62691279/how-to-disable-tokenizers-parallelism-true-false-warning/72926996#72926996\r\n\r\n Thank you!", "Though each notebook runs fine by itself, I get this warning when running multiple notebooks via `nbdev_test` (https://github.com/fastai/nbdev). Shortly afterwards it crashes due to out-of-memory. \r\n\r\nI assume it has something to do with multiprocessing in `nbdev_test`, even when setting `--n_workers 1`.\r\n\r\nThis gets a warning about disabling parallelism to avoid locks:\r\n> ```nbdev_test --n_workers 1 --pause 10 --do_print --file_glob \"*nb\"```\r\n\r\nThis works fine:\r\n> ```$ for x in `ls nbs/*nb`; do nbdev_test --n_workers 1 --do_print --path \"$x\"; done```" ]

[ { "id": 1314768611, "node_id": "MDU6TGFiZWwxMzE0NzY4NjEx", "url": "https://api.github.com/repos/huggingface/transformers/labels/wontfix", "name": "wontfix", "color": "ffffff", "default": true, "description": null } ]

[]

[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

[]

[ { "login": "sshleifer", "id": 6045025, "node_id": "MDQ6VXNlcjYwNDUwMjU=", "avatar_url": "https://avatars.githubusercontent.com/u/6045025?v=4", "gravatar_id": "", "url": "https://api.github.com/users/sshleifer", "html_url": "https://github.com/sshleifer", "followers_url": "https://api.github.com/users/sshleifer/followers", "following_url": "https://api.github.com/users/sshleifer/following{/other_user}", "gists_url": "https://api.github.com/users/sshleifer/gists{/gist_id}", "starred_url": "https://api.github.com/users/sshleifer/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/sshleifer/subscriptions", "organizations_url": "https://api.github.com/users/sshleifer/orgs", "repos_url": "https://api.github.com/users/sshleifer/repos", "events_url": "https://api.github.com/users/sshleifer/events{/privacy}", "received_events_url": "https://api.github.com/users/sshleifer/received_events", "type": "User", "site_admin": false } ]

[ "Use the standard `T5Tokenizer.from_pretrained('t5-base')`", "and I would love to hear your results!", "The outputs of t5-base-cnn are good! Will let you know when I run over a bigger dataset.\r\nMy doubt is how many epochs is ideal for fine-tuning t5 models over cnn/dm?\r\nMy t5-small fine-tuned over cnn/dm code(number of epochs ran : 1) produces okayish results but not that great. Even some sentences in the output didn't get completed at the end and looked as if it's cut.", "I don't know how many epochs to train t5-small for, but our new `finetune.py` tracks the validation rouge 2 score. Usually when that stops increasing, the model will not further improve.\r\nAlso, since epochs are so long, there is a `--val_check_interval` argument that you can use to check this statistic more frequently than the default, every epoch.", "Thank you, Sam. You solve my problem too. Benefit a lot from your work.", "Happy to help. Closing this for now, feel free to open a new issue if you run into more problems!", "Hello everyone!\r\n\r\nI used direct T5Tokenizer.from_pretrained('t5-base')... however, I got the following error:\r\n\r\nOSError: Model name 't5-base' was not found in tokenizers model name list (t5-small, t5-base, t5-large, t5-3b, t5-11b). We assumed 't5-base' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\r\n\r\nHow can I resolve this issue? or from where can I download the model manually?\r\n\r\nThank you in advance\r\n", "I tried to generate results using ```sshleifer/t5-base-cnn``` and changed the tokenizer to ```tokenizer = T5Tokenizer.from_pretrained('t5-base')``` and failed. \r\n\r\nMy code:\r\n```\r\npython run_eval.py sshleifer/t5-base-cnn $DATA_DIR/test.source $OUTPUT_FILE \\\r\n --reference_path $DATA_DIR/test.target \\\r\n --task summarization \\\r\n --device cuda \\\r\n --fp16 \\\r\n --bs 32 \\\r\n```\r\n\r\nFollowing is the error message:\r\n\r\n```\r\nTraceback (most recent call last):\r\n File \"run_eval.py\", line 127, in <module>\r\n run_generate()\r\n File \"run_eval.py\", line 112, in run_generate\r\n checkpoint_path=args.checkpoint_path,\r\n File \"run_eval.py\", line 63, in generate_summaries_or_translations\r\n **gen_kwargs,\r\n File \"/home/rachelzheng/www-joy/venv/lib/python3.6/site-packages/torch/autograd/grad_mode.py\", line 49, in decorate_no_grad\r\n return func(*args, **kwargs)\r\n File \"/home/rachelzheng/www-joy/venv/lib/python3.6/site-packages/transformers/generation_utils.py\", line 480, in generate\r\n model_kwargs=model_kwargs,\r\n File \"/home/rachelzheng/www-joy/venv/lib/python3.6/site-packages/transformers/generation_utils.py\", line 795, in _generate_beam_search\r\n input_ids = torch.cat([input_ids, beam_tokens.unsqueeze(1)], dim=-1)\r\nRuntimeError: cuda runtime error (710) : device-side assert triggered at /pytorch/aten/src/THC/generic/THCTensorMath.cu:196\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[32,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[33,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[34,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[35,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[36,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[37,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[38,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[39,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[40,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[41,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[42,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[43,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[44,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[45,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[46,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[47,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[48,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[49,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[50,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[51,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[52,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[53,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[54,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[55,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[56,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[57,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[58,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[59,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[60,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[61,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[62,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[63,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[64,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[65,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[66,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[67,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[68,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[69,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[70,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[71,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[72,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[73,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[74,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[75,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[76,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[77,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[78,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[79,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[80,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[81,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[82,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[83,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[84,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[85,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[86,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[87,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[88,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[89,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[90,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[91,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[92,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[93,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[94,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[95,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[96,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[97,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[98,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[99,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[100,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[101,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[102,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[103,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[104,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[105,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[106,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[107,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[108,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[109,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[110,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[111,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[112,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[113,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[114,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[115,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[116,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[117,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[118,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[119,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[120,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[121,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[122,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[123,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[124,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[125,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[126,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[127,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[0,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[1,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[2,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[3,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[4,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[5,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[6,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[7,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[8,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[9,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[10,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[11,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[12,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[13,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[14,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[15,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[16,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[17,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[18,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[19,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[20,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[21,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[22,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[23,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[24,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[25,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[26,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[27,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[28,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[29,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[30,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: lambda [](int)->auto::operator()(int)->auto: block: [0,0,0], thread:[31,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && \"index out of bounds\"` failed.\r\n```", "Okay it looks like ```fp16``` leads to the problem. Remove ```--fp16``` solves my problem." ]

[ { "id": 1314768611, "node_id": "MDU6TGFiZWwxMzE0NzY4NjEx", "url": "https://api.github.com/repos/huggingface/transformers/labels/wontfix", "name": "wontfix", "color": "ffffff", "default": true, "description": null } ]

[]

[ "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n" ]

[]

[ { "login": "n1t0", "id": 1217986, "node_id": "MDQ6VXNlcjEyMTc5ODY=", "avatar_url": "https://avatars.githubusercontent.com/u/1217986?v=4", "gravatar_id": "", "url": "https://api.github.com/users/n1t0", "html_url": "https://github.com/n1t0", "followers_url": "https://api.github.com/users/n1t0/followers", "following_url": "https://api.github.com/users/n1t0/following{/other_user}", "gists_url": "https://api.github.com/users/n1t0/gists{/gist_id}", "starred_url": "https://api.github.com/users/n1t0/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/n1t0/subscriptions", "organizations_url": "https://api.github.com/users/n1t0/orgs", "repos_url": "https://api.github.com/users/n1t0/repos", "events_url": "https://api.github.com/users/n1t0/events{/privacy}", "received_events_url": "https://api.github.com/users/n1t0/received_events", "type": "User", "site_admin": false } ]

[ "Hi, ok I can reproduce, this is a bug in the `AddedToken`class of `huggingface/tokenizers`. Moving this up." ]

[]

[]

[]

[]

[]

[ "Hi! This is because the return of `tokenizer('sentence embeddings from t5 model', return_tensors=\"pt\")` is a dict containing values that can be used by the model. It's not a tensor, so it's not `input_ids`.\r\n\r\nChange the following line:\r\n```py\r\ntokenizer('sentence embeddings from t5 model', return_tensors=\"pt\")\r\n```\r\nto\r\n```py\r\ntokenizer('sentence embeddings from t5 model', return_tensors=\"pt\")[\"input_ids\"]\r\n```\r\nto make it work.\r\n\r\nYou can check the documentation [here](https://huggingface.co/transformers/main_classes/tokenizer.html#transformers.PreTrainedTokenizer.__call__)." ]

[ { "id": 1834056635, "node_id": "MDU6TGFiZWwxODM0MDU2NjM1", "url": "https://api.github.com/repos/huggingface/transformers/labels/Core:%20Tokenization", "name": "Core: Tokenization", "color": "FF4446", "default": false, "description": "Internals of the library; Tokenization." } ]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5479?src=pr&el=h1) Report\n> Merging [#5479](https://codecov.io/gh/huggingface/transformers/pull/5479?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ef0e9d806c51059b07b98cb0279a20d3ba3cbc1d&el=desc) will **increase** coverage by `0.43%`.\n> The diff coverage is `89.53%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5479?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5479 +/- ##\n==========================================\n+ Coverage 77.36% 77.80% +0.43% \n==========================================\n Files 141 141 \n Lines 24617 24632 +15 \n==========================================\n+ Hits 19045 19164 +119 \n+ Misses 5572 5468 -104 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5479?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/5479/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `93.60% <89.28%> (-0.62%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5479/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHMucHk=) | `91.16% <100.00%> (+0.94%)` | :arrow_up: |\n| [src/transformers/tokenization\\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/5479/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYWxiZXJ0LnB5) | `28.84% <0.00%> (-58.66%)` | :arrow_down: |\n| [src/transformers/configuration\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5479/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3V0aWxzLnB5) | `96.40% <0.00%> (+0.71%)` | :arrow_up: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5479/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.43% <0.00%> (+1.25%)` | :arrow_up: |\n| [src/transformers/tokenization\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/5479/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYXV0by5weQ==) | `97.77% <0.00%> (+2.22%)` | :arrow_up: |\n| [src/transformers/tokenization\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/5479/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYmVydC5weQ==) | `92.23% <0.00%> (+2.28%)` | :arrow_up: |\n| [src/transformers/tokenization\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5479/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fcm9iZXJ0YS5weQ==) | `98.63% <0.00%> (+4.10%)` | :arrow_up: |\n| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/5479/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `55.79% <0.00%> (+27.58%)` | :arrow_up: |\n| ... and [1 more](https://codecov.io/gh/huggingface/transformers/pull/5479/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5479?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5479?src=pr&el=footer). Last update [ef0e9d8...ecdc965](https://codecov.io/gh/huggingface/transformers/pull/5479?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[]

[]

[ "Hi, overflowing tokens are handled differently between slow and fast tokenizers with fast tokenizers having better support.\r\nWhich kind of tokenizer are you using?", "I am using the fast tokenizers ", "Ok, currently we don't handle overflowing in fast tokenizers with this processing script.\r\nThis is on the short term roadmap though." ]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5477?src=pr&el=h1) Report\n> Merging [#5477](https://codecov.io/gh/huggingface/transformers/pull/5477?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/58cca47c16149e43d1b516623d59e3c5d97f695e&el=desc) will **increase** coverage by `0.41%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5477?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5477 +/- ##\n==========================================\n+ Coverage 77.83% 78.25% +0.41% \n==========================================\n Files 141 141 \n Lines 24634 24634 \n==========================================\n+ Hits 19175 19278 +103 \n+ Misses 5459 5356 -103 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5477?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5477/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9yb2JlcnRhLnB5) | `43.47% <0.00%> (-49.57%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5477/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `81.09% <0.00%> (+1.37%)` | :arrow_up: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5477/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.71% <0.00%> (+1.50%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5477/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `94.98% <0.00%> (+74.19%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5477?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5477?src=pr&el=footer). Last update [58cca47...f44de41](https://codecov.io/gh/huggingface/transformers/pull/5477?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Btw: would be awesome so see a token classification example 😅", "Hi @JetRunner, thanks for the review! I have updated according to your suggestions.", "2 checks fail, however they don't seem relevant to my commits.", "@LysandreJik Thanks for the comments and I've updated accordingly!" ]

[ { "id": 1108649053, "node_id": "MDU6TGFiZWwxMTA4NjQ5MDUz", "url": "https://api.github.com/repos/huggingface/transformers/labels/Help%20wanted", "name": "Help wanted", "color": "008672", "default": false, "description": "Extra attention is needed, help appreciated" } ]

[ { "login": "sshleifer", "id": 6045025, "node_id": "MDQ6VXNlcjYwNDUwMjU=", "avatar_url": "https://avatars.githubusercontent.com/u/6045025?v=4", "gravatar_id": "", "url": "https://api.github.com/users/sshleifer", "html_url": "https://github.com/sshleifer", "followers_url": "https://api.github.com/users/sshleifer/followers", "following_url": "https://api.github.com/users/sshleifer/following{/other_user}", "gists_url": "https://api.github.com/users/sshleifer/gists{/gist_id}", "starred_url": "https://api.github.com/users/sshleifer/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/sshleifer/subscriptions", "organizations_url": "https://api.github.com/users/sshleifer/orgs", "repos_url": "https://api.github.com/users/sshleifer/repos", "events_url": "https://api.github.com/users/sshleifer/events{/privacy}", "received_events_url": "https://api.github.com/users/sshleifer/received_events", "type": "User", "site_admin": false } ]

[ "Do you still need help? I can help out and contribute here. ", "Yes that would be super helpful! The goal is to avoid using so much CPU memory here:\r\nhttps://github.com/huggingface/transformers/blob/353b8f1e7a7361c0afd9e391381bc226b4a5ca8f/examples/seq2seq/utils.py#L101\r\n\r\nby only reading a few batches from disk at a time instead of all at once. Will probably require saving in a different format.\r\nMaybe something like this:\r\nhttps://github.com/pytorch/fairseq/blob/f0a61a2774aff2efbc1adb0b5daee346a8401605/fairseq/data/data_utils.py#L55\r\n\r\nLet me know if you need more info!", "Great! \r\nMy idea is to lazily read & encode just the required line numbers from the file when `__getitem__` is called with an index. For this we could create a map of {example number: line numbers} to read. Let me know what you think.", "Sounds reasonable. What does fairseq do?", "Your approach sounds good, feel free to get started.\r\n\r\nAnother approach would be not pad inputs when they are getting cached and then make a batch at load time. ", "I think fairseq had the data in multiple files instead of one big one. Sounds good - I am working on it. Will share when I have a tested version. ", "Couple of questions : I plan to get rid of the self.source variable; \r\n1. can I get rid of this property?https://github.com/huggingface/transformers/blob/353b8f1e7a7361c0afd9e391381bc226b4a5ca8f/examples/seq2seq/utils.py#L146-L148\r\n\r\n2. Any ideas on how to use the sampler without the full dataset? In general shuffling and sampling may be limited with lazy datasets: although you should be able to use a random sampler in your loader.\r\nhttps://github.com/huggingface/transformers/blob/353b8f1e7a7361c0afd9e391381bc226b4a5ca8f/examples/seq2seq/utils.py#L155", "@sshleifer I have a working solution that works for the rest of the training loop and passes the tests. See [here](https://github.com/huggingface/transformers/compare/master...Pradhy729:lazy_loading_seq2seq)\r\nJust need input on my points above. Let me know.", "1) You can get rid of `src_lens` and `tgt_lens`, they are unused afaict\r\n\r\n2) I would suggest trying to store the len of each example, (tokenized or untokenized, but not padded), and passing that to `SortishSampler` instead of `self.source`, and then changing\r\n`def key(self, i): len(self.data[i])` -> `def key(self, i): self.data[i]`.\r\n\r\nhttps://github.com/huggingface/transformers/blob/7e86d070c0bbed949b5c922f914f0fec44af72d4/examples/seq2seq/utils.py#L203.\r\n\r\n", "Like https://github.com/huggingface/transformers/pull/5818", "Got it. Good idea!" ]

[]

[]

[ "142 AutoTokenizer Failures (the original 35 +107 more).\r\nWhat would help with the `sshleifer` ones (at least) is if I could somehow say \"this is the same as the `BartTokenizer` without uploading the same files all over again. Sadly, S3 does not support symlinks.\r\n\r\n```\r\n{'DeBERTa/base': ('Unrecognized model in DeBERTa/base. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'DeBERTa/large': ('Unrecognized model in DeBERTa/large. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'Huntersx/cola_model': (\"Model name 'Huntersx/cola_model' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'Huntersx/cola_model' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'Itcast/cnc_output': ('Unrecognized model in Itcast/cnc_output. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'JerryQu/v2 distilgpt2': (\"Model name 'JerryQu/v2 distilgpt2' was not found in tokenizers model name list (gpt2, gpt2-medium, gpt2-large, gpt2-xl, distilgpt2). We assumed 'JerryQu/v2 distilgpt2' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'Narsil/fr_pretrained': ('Unrecognized model in Narsil/fr_pretrained. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'Narsil/pretrained': ('Unrecognized model in Narsil/pretrained. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'Narsil/pretrained2': ('Unrecognized model in Narsil/pretrained2. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'PubChimps/dl-bert': (\"Model name 'PubChimps/dl-bert' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'PubChimps/dl-bert' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'Tereveni-AI/gpt2-124M-uk-fiction': ('expected str, bytes or os.PathLike object, not NoneType',),\r\n 'WikinewsSum/bart-large-multi-combine-wiki-news': ('expected str, bytes or os.PathLike object, not NoneType',),\r\n 'WikinewsSum/bert2bert-multi-de-wiki-news': (\"Unrecognized configuration class <class 'transformers.configuration_encoder_decoder.EncoderDecoderConfig'> to build an AutoTokenizer.\\nModel type should be one of RetriBertConfig, T5Config, MobileBertConfig, DistilBertConfig, AlbertConfig, CamembertConfig, MBartConfig, XLMRobertaConfig, MarianConfig, BartConfig, LongformerConfig, RobertaConfig, ReformerConfig, ElectraConfig, BertConfig, OpenAIGPTConfig, GPT2Config, TransfoXLConfig, XLNetConfig, FlaubertConfig, XLMConfig, CTRLConfig.\",),\r\n 'WikinewsSum/bert2bert-multi-en-wiki-news': (\"Unrecognized configuration class <class 'transformers.configuration_encoder_decoder.EncoderDecoderConfig'> to build an AutoTokenizer.\\nModel type should be one of RetriBertConfig, T5Config, MobileBertConfig, DistilBertConfig, AlbertConfig, CamembertConfig, MBartConfig, XLMRobertaConfig, MarianConfig, BartConfig, LongformerConfig, RobertaConfig, ReformerConfig, ElectraConfig, BertConfig, OpenAIGPTConfig, GPT2Config, TransfoXLConfig, XLNetConfig, FlaubertConfig, XLMConfig, CTRLConfig.\",),\r\n 'WikinewsSum/bert2bert-multi-fr-wiki-news': (\"Unrecognized configuration class <class 'transformers.configuration_encoder_decoder.EncoderDecoderConfig'> to build an AutoTokenizer.\\nModel type should be one of RetriBertConfig, T5Config, MobileBertConfig, DistilBertConfig, AlbertConfig, CamembertConfig, MBartConfig, XLMRobertaConfig, MarianConfig, BartConfig, LongformerConfig, RobertaConfig, ReformerConfig, ElectraConfig, BertConfig, OpenAIGPTConfig, GPT2Config, TransfoXLConfig, XLNetConfig, FlaubertConfig, XLMConfig, CTRLConfig.\",),\r\n 'abryee/TigXLNet': ('`d_head` (64) should be equal to `d_model // n_head` (48)',),\r\n 'adamlin/ClinicalBert_all_notes': ('Unrecognized model in adamlin/ClinicalBert_all_notes. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'adamlin/ClinicalBert_disch': ('Unrecognized model in adamlin/ClinicalBert_disch. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'adamlin/NCBI_BERT_pubmed_mimic_uncased_base_transformers': ('Unrecognized model in adamlin/NCBI_BERT_pubmed_mimic_uncased_base_transformers. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'adamlin/NCBI_BERT_pubmed_mimic_uncased_large_transformers': ('Unrecognized model in adamlin/NCBI_BERT_pubmed_mimic_uncased_large_transformers. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'ahotrod/roberta_large_squad2': ('expected str, bytes or os.PathLike object, not NoneType',),\r\n 'aicast/bert_finetuning_test': ('stat: path should be string, bytes, os.PathLike or integer, not NoneType',),\r\n 'airKlizz/bart-large-multi-combine-wiki-news': ('expected str, bytes or os.PathLike object, not NoneType',),\r\n 'airKlizz/bert2bert-multi-de-wiki-news': (\"Unrecognized configuration class <class 'transformers.configuration_encoder_decoder.EncoderDecoderConfig'> to build an AutoTokenizer.\\nModel type should be one of RetriBertConfig, T5Config, MobileBertConfig, DistilBertConfig, AlbertConfig, CamembertConfig, MBartConfig, XLMRobertaConfig, MarianConfig, BartConfig, LongformerConfig, RobertaConfig, ReformerConfig, ElectraConfig, BertConfig, OpenAIGPTConfig, GPT2Config, TransfoXLConfig, XLNetConfig, FlaubertConfig, XLMConfig, CTRLConfig.\",),\r\n 'airKlizz/bert2bert-multi-en-wiki-news': (\"Unrecognized configuration class <class 'transformers.configuration_encoder_decoder.EncoderDecoderConfig'> to build an AutoTokenizer.\\nModel type should be one of RetriBertConfig, T5Config, MobileBertConfig, DistilBertConfig, AlbertConfig, CamembertConfig, MBartConfig, XLMRobertaConfig, MarianConfig, BartConfig, LongformerConfig, RobertaConfig, ReformerConfig, ElectraConfig, BertConfig, OpenAIGPTConfig, GPT2Config, TransfoXLConfig, XLNetConfig, FlaubertConfig, XLMConfig, CTRLConfig.\",),\r\n 'airKlizz/bert2bert-multi-fr-wiki-news': (\"Unrecognized configuration class <class 'transformers.configuration_encoder_decoder.EncoderDecoderConfig'> to build an AutoTokenizer.\\nModel type should be one of RetriBertConfig, T5Config, MobileBertConfig, DistilBertConfig, AlbertConfig, CamembertConfig, MBartConfig, XLMRobertaConfig, MarianConfig, BartConfig, LongformerConfig, RobertaConfig, ReformerConfig, ElectraConfig, BertConfig, OpenAIGPTConfig, GPT2Config, TransfoXLConfig, XLNetConfig, FlaubertConfig, XLMConfig, CTRLConfig.\",),\r\n 'allegro/herbert-klej-cased-v1': (\"Model name 'allegro/herbert-klej-cased-v1' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'allegro/herbert-klej-cased-v1' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'beyhan/checkpoint-3750': (\"Model name 'beyhan/checkpoint-3750' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'beyhan/checkpoint-3750' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'camembert/camembert-base': (\"Model name 'camembert/camembert-base' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'camembert/camembert-base' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'castorini/monot5-base-msmarco': (\"Model name 'castorini/monot5-base-msmarco' was not found in tokenizers model name list (t5-small, t5-base, t5-large, t5-3b, t5-11b). We assumed 'castorini/monot5-base-msmarco' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'chrisliu298/arxiv_ai_gpt2': ('expected str, bytes or os.PathLike object, not NoneType',),\r\n 'clue/albert_chinese_small': (\"Model name 'clue/albert_chinese_small' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'clue/albert_chinese_small' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'clue/albert_chinese_tiny': (\"Model name 'clue/albert_chinese_tiny' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'clue/albert_chinese_tiny' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'clue/roberta_chinese_3L312_clue_tiny': (\"Model name 'clue/roberta_chinese_3L312_clue_tiny' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'clue/roberta_chinese_3L312_clue_tiny' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'clue/roberta_chinese_3L768_clue_tiny': (\"Model name 'clue/roberta_chinese_3L768_clue_tiny' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'clue/roberta_chinese_3L768_clue_tiny' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'clue/roberta_chinese_base': (\"Model name 'clue/roberta_chinese_base' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'clue/roberta_chinese_base' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'clue/roberta_chinese_clue_large': (\"Model name 'clue/roberta_chinese_clue_large' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'clue/roberta_chinese_clue_large' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'clue/roberta_chinese_clue_tiny': (\"Model name 'clue/roberta_chinese_clue_tiny' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'clue/roberta_chinese_clue_tiny' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'clue/roberta_chinese_large': (\"Model name 'clue/roberta_chinese_large' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'clue/roberta_chinese_large' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'clue/roberta_chinese_pair_large': (\"Model name 'clue/roberta_chinese_pair_large' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'clue/roberta_chinese_pair_large' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'clue/roberta_chinese_pair_tiny': (\"Model name 'clue/roberta_chinese_pair_tiny' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'clue/roberta_chinese_pair_tiny' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'codegram/calbert-base-uncased': (\"Model name 'codegram/calbert-base-uncased' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'codegram/calbert-base-uncased' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'codegram/calbert-tiny-uncased': (\"Model name 'codegram/calbert-tiny-uncased' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'codegram/calbert-tiny-uncased' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'damien-ir/discriminator': (\"Model name 'damien-ir/discriminator' was not found in tokenizers model name list (google/electra-small-generator, google/electra-base-generator, google/electra-large-generator, google/electra-small-discriminator, google/electra-base-discriminator, google/electra-large-discriminator). We assumed 'damien-ir/discriminator' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'dccuchile/cased': ('Unrecognized model in dccuchile/cased. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'dccuchile/uncased': ('Unrecognized model in dccuchile/uncased. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'denpa92/bert-base-cantonese': (\"Model name 'denpa92/bert-base-cantonese' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'denpa92/bert-base-cantonese' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'djstrong/bg_cs_pl_ru_cased_L-12_H-768_A-12': ('Unrecognized model in djstrong/bg_cs_pl_ru_cased_L-12_H-768_A-12. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'dslim23/bert-base-cased-NER-conll-2003': (\"Model name 'dslim23/bert-base-cased-NER-conll-2003' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'dslim23/bert-base-cased-NER-conll-2003' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'elgeish/cs224n-squad2.0-distilbert-base-uncased': ('stat: path should be string, bytes, os.PathLike or integer, not NoneType',),\r\n 'elgeish/cs224n-squad2.0-roberta-base': ('expected str, bytes or os.PathLike object, not NoneType',),\r\n 'facebook/dpr-ctx_encoder-single-nq-base': ('dpr',),\r\n 'facebook/dpr-question_encoder-single-nq-base': ('dpr',),\r\n 'facebook/dpr-reader-single-nq-base': ('dpr',),\r\n 'gaochangkuan/model_dir': ('expected str, bytes or os.PathLike object, not NoneType',),\r\n 'google/reformer-enwik8': (\"Model name 'google/reformer-enwik8' was not found in tokenizers model name list (google/reformer-crime-and-punishment). We assumed 'google/reformer-enwik8' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'healx/gpt-2-pubmed-large': ('Unrecognized model in healx/gpt-2-pubmed-large. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'healx/gpt-2-pubmed-medium': ('Unrecognized model in healx/gpt-2-pubmed-medium. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'hfl/chinese-roberta-wwm-ext-large': ('expected str, bytes or os.PathLike object, not NoneType',),\r\n 'hfl/chinese-roberta-wwm-ext': ('expected str, bytes or os.PathLike object, not NoneType',),\r\n 'hfl/rbt3': ('Unrecognized model in hfl/rbt3. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'hfl/rbtl3': ('Unrecognized model in hfl/rbtl3. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'huseinzol05/bert-base-bahasa-cased': ('stat: path should be string, bytes, os.PathLike or integer, not NoneType',),\r\n 'huseinzol05/tiny-bert-bahasa-cased': ('stat: path should be string, bytes, os.PathLike or integer, not NoneType',),\r\n 'lhoestq/distilbert-base-uncased-finetuned-absa-as': (\"Model name 'lhoestq/distilbert-base-uncased-finetuned-absa-as' was not found in tokenizers model name list (distilbert-base-uncased, distilbert-base-uncased-distilled-squad, distilbert-base-cased, distilbert-base-cased-distilled-squad, distilbert-base-german-cased, distilbert-base-multilingual-cased). We assumed 'lhoestq/distilbert-base-uncased-finetuned-absa-as' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'lonePatient/albert_chinese_small': (\"Model name 'lonePatient/albert_chinese_small' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'lonePatient/albert_chinese_small' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'lonePatient/roberta_chinese_clue_tiny': (\"Model name 'lonePatient/roberta_chinese_clue_tiny' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'lonePatient/roberta_chinese_clue_tiny' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'm-polignano-uniba/bert_uncased_L-12_H-768_A-12_italian_alberto': (\"Model name 'm-polignano-uniba/bert_uncased_L-12_H-768_A-12_italian_alberto' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'm-polignano-uniba/bert_uncased_L-12_H-768_A-12_italian_alberto' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'microsoft/Multilingual-MiniLM-L12-H384': ('stat: path should be string, bytes, os.PathLike or integer, not NoneType',),\r\n 'microsoft/unilm-base-cased': ('Unrecognized model in microsoft/unilm-base-cased. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'microsoft/unilm-large-cased': ('Unrecognized model in microsoft/unilm-large-cased. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'moumeneb1/bert-base-multilingual-cased-ecology_crisis': (\"Model name 'moumeneb1/bert-base-multilingual-cased-ecology_crisis' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'moumeneb1/bert-base-multilingual-cased-ecology_crisis' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'moumeneb1/flaubert-base-cased-ecology_crisis': (\"Model name 'moumeneb1/flaubert-base-cased-ecology_crisis' was not found in tokenizers model name list (flaubert/flaubert_small_cased, flaubert/flaubert_base_uncased, flaubert/flaubert_base_cased, flaubert/flaubert_large_cased). We assumed 'moumeneb1/flaubert-base-cased-ecology_crisis' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'mrm8488/bert-uncased-finetuned-qnli': (\"Model name 'mrm8488/bert-uncased-finetuned-qnli' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'mrm8488/bert-uncased-finetuned-qnli' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'mrm8488/prunebert-base-uncased-finepruned-topK-squadv2': ('masked_bert',),\r\n 'mrm8488/prunebert-multi-uncased-finepruned-l0-reg-tydiqa-for-xqa': ('masked_bert',),\r\n 'mrm8488/prunebert-multi-uncased-finepruned-magnitude-tydiqa-for-xqa': ('masked_bert',),\r\n 'mrm8488/prunebert-multi-uncased-finepruned-soft-movement-tydiqa-for-xqa': ('masked_bert',),\r\n 'mrm8488/prunebert-multi-uncased-finepruned-topK-tydiqa-for-xqa': ('masked_bert',),\r\n 'mrm8488/prunebert-multi-uncased-finepruned-tydiqa-for-xqa': ('masked_bert',),\r\n 'mrm8488/roberta-large-finetuned-wsc': ('expected str, bytes or os.PathLike object, not NoneType',),\r\n 'mrm8488/spanbert-base-finetuned-squadv1': (\"Model name 'mrm8488/spanbert-base-finetuned-squadv1' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'mrm8488/spanbert-base-finetuned-squadv1' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'mrm8488/spanbert-base-finetuned-squadv2': (\"Model name 'mrm8488/spanbert-base-finetuned-squadv2' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'mrm8488/spanbert-base-finetuned-squadv2' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'mrm8488/spanbert-large-finetuned-squadv1': (\"Model name 'mrm8488/spanbert-large-finetuned-squadv1' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'mrm8488/spanbert-large-finetuned-squadv1' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'mrm8488/spanbert-large-finetuned-squadv2': (\"Model name 'mrm8488/spanbert-large-finetuned-squadv2' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'mrm8488/spanbert-large-finetuned-squadv2' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'oda/music5': ('Unrecognized model in oda/music5. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'patrickvonplaten/reformer-random': (\"Model name 'patrickvonplaten/reformer-random' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'patrickvonplaten/reformer-random' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'patrickvonplaten/reformer-tiny-random': (\"Model name 'patrickvonplaten/reformer-tiny-random' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'patrickvonplaten/reformer-tiny-random' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'pertschuk/0_RoBERTa': ('Unrecognized model in pertschuk/0_RoBERTa. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'pertschuk/albert-base-squad-classifier-ms': (\"Model name 'pertschuk/albert-base-squad-classifier-ms' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'pertschuk/albert-base-squad-classifier-ms' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'pertschuk/albert-base-squad-classifier': (\"Model name 'pertschuk/albert-base-squad-classifier' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'pertschuk/albert-base-squad-classifier' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'pertschuk/albert-intent-model-v3': (\"Model name 'pertschuk/albert-intent-model-v3' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'pertschuk/albert-intent-model-v3' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'radha1258/save': ('Unrecognized model in radha1258/save. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'ramsrigouthamg/t5_boolean_questions': (\"Model name 'ramsrigouthamg/t5_boolean_questions' was not found in tokenizers model name list (t5-small, t5-base, t5-large, t5-3b, t5-11b). We assumed 'ramsrigouthamg/t5_boolean_questions' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'ramsrigouthamg/t5_paraphraser': (\"Model name 'ramsrigouthamg/t5_paraphraser' was not found in tokenizers model name list (t5-small, t5-base, t5-large, t5-3b, t5-11b). We assumed 'ramsrigouthamg/t5_paraphraser' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'ramsrigouthamg/t5_squad': (\"Model name 'ramsrigouthamg/t5_squad' was not found in tokenizers model name list (t5-small, t5-base, t5-large, t5-3b, t5-11b). We assumed 'ramsrigouthamg/t5_squad' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'ran/c10': (\"Model name 'ran/c10' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'ran/c10' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'ran/c9': (\"Model name 'ran/c9' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'ran/c9' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'ran/h1': (\"Model name 'ran/h1' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'ran/h1' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'ran/y7': (\"Model name 'ran/y7' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'ran/y7' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization': (\"Model name 'remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'remi/bertabs-finetuned-extractive-abstractive-summarization': (\"Model name 'remi/bertabs-finetuned-extractive-abstractive-summarization' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'remi/bertabs-finetuned-extractive-abstractive-summarization' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'remi/bertabs-finetuned-xsum-extractive-abstractive-summarization': (\"Model name 'remi/bertabs-finetuned-xsum-extractive-abstractive-summarization' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'remi/bertabs-finetuned-xsum-extractive-abstractive-summarization' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'savasy/checkpoint-1250': (\"Model name 'savasy/checkpoint-1250' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'savasy/checkpoint-1250' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'savasy/checkpoint-1875': (\"Model name 'savasy/checkpoint-1875' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'savasy/checkpoint-1875' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'savasy/model': (\"Model name 'savasy/model' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, TurkuNLP/bert-base-finnish-cased-v1, TurkuNLP/bert-base-finnish-uncased-v1, wietsedv/bert-base-dutch-cased). We assumed 'savasy/model' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'schmidek/electra-small-cased': (\"Model name 'schmidek/electra-small-cased' was not found in tokenizers model name list (google/electra-small-generator, google/electra-base-generator, google/electra-large-generator, google/electra-small-discriminator, google/electra-base-discriminator, google/electra-large-discriminator). We assumed 'schmidek/electra-small-cased' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'shauryr/arqmath-roberta-base-1.5M': (\"Model name 'shauryr/arqmath-roberta-base-1.5M' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'shauryr/arqmath-roberta-base-1.5M' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'shauryr/arqmath-roberta-base-2M': (\"Model name 'shauryr/arqmath-roberta-base-2M' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'shauryr/arqmath-roberta-base-2M' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'shauryr/arqmath-roberta-base': (\"Model name 'shauryr/arqmath-roberta-base' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'shauryr/arqmath-roberta-base' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'shauryr/checkpoint-475000': (\"Model name 'shauryr/checkpoint-475000' was not found in tokenizers model name list (roberta-base, roberta-large, roberta-large-mnli, distilroberta-base, roberta-base-openai-detector, roberta-large-openai-detector). We assumed 'shauryr/checkpoint-475000' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'shoarora/alectra-small-owt': (\"Model name 'shoarora/alectra-small-owt' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'shoarora/alectra-small-owt' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'spentaur/yelp': (\"Model name 'spentaur/yelp' was not found in tokenizers model name list (distilbert-base-uncased, distilbert-base-uncased-distilled-squad, distilbert-base-cased, distilbert-base-cased-distilled-squad, distilbert-base-german-cased, distilbert-base-multilingual-cased). We assumed 'spentaur/yelp' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/blenderbot-3B': ('blenderbot',),\r\n 'sshleifer/cnn_student_d6': (\"Model name 'sshleifer/cnn_student_d6' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/cnn_student_d6' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/mbart-large-cc25': (\"Model name 'sshleifer/mbart-large-cc25' was not found in tokenizers model name list (facebook/mbart-large-en-ro, facebook/mbart-large-cc25). We assumed 'sshleifer/mbart-large-cc25' was a path, a model identifier, or url to a directory containing vocabulary files named ['sentencepiece.bpe.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/mbart-large-en-ro': (\"Model name 'sshleifer/mbart-large-en-ro' was not found in tokenizers model name list (facebook/mbart-large-en-ro, facebook/mbart-large-cc25). We assumed 'sshleifer/mbart-large-en-ro' was a path, a model identifier, or url to a directory containing vocabulary files named ['sentencepiece.bpe.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_cnn_12_3': (\"Model name 'sshleifer/student_cnn_12_3' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_cnn_12_3' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_cnn_12_6': (\"Model name 'sshleifer/student_cnn_12_6' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_cnn_12_6' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_cnn_12_9': (\"Model name 'sshleifer/student_cnn_12_9' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_cnn_12_9' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_cnn_6_6': (\"Model name 'sshleifer/student_cnn_6_6' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_cnn_6_6' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_cnn_9_12': (\"Model name 'sshleifer/student_cnn_9_12' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_cnn_9_12' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_cnn_9_9': (\"Model name 'sshleifer/student_cnn_9_9' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_cnn_9_9' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_xsum_12_3': (\"Model name 'sshleifer/student_xsum_12_3' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_xsum_12_3' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_xsum_12_4': (\"Model name 'sshleifer/student_xsum_12_4' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_xsum_12_4' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_xsum_12_6': (\"Model name 'sshleifer/student_xsum_12_6' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_xsum_12_6' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_xsum_12_9': (\"Model name 'sshleifer/student_xsum_12_9' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_xsum_12_9' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_xsum_3_12': (\"Model name 'sshleifer/student_xsum_3_12' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_xsum_3_12' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_xsum_6_12': (\"Model name 'sshleifer/student_xsum_6_12' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_xsum_6_12' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_xsum_6_6': (\"Model name 'sshleifer/student_xsum_6_6' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_xsum_6_6' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_xsum_9_12': (\"Model name 'sshleifer/student_xsum_9_12' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_xsum_9_12' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/student_xsum_9_9': (\"Model name 'sshleifer/student_xsum_9_9' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/student_xsum_9_9' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/t5-base-cnn': (\"Model name 'sshleifer/t5-base-cnn' was not found in tokenizers model name list (t5-small, t5-base, t5-large, t5-3b, t5-11b). We assumed 'sshleifer/t5-base-cnn' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'sshleifer/tinier_bart': (\"Model name 'sshleifer/tinier_bart' was not found in tokenizers model name list (facebook/bart-base, facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum, yjernite/bart_eli5). We assumed 'sshleifer/tinier_bart' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'subbareddyiiit/iiit': ('Unrecognized model in subbareddyiiit/iiit. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'subbareddyiiit/tftelugu': ('Unrecognized model in subbareddyiiit/tftelugu. Should have a `model_type` key in its config.json, or contain one of the following strings in its name: retribert, t5, mobilebert, distilbert, albert, camembert, xlm-roberta, marian, mbart, bart, reformer, longformer, roberta, flaubert, bert, openai-gpt, gpt2, transfo-xl, xlnet, xlm, ctrl, electra, encoder-decoder',),\r\n 'voidful/albert_chinese_base': (\"Model name 'voidful/albert_chinese_base' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'voidful/albert_chinese_base' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'voidful/albert_chinese_large': (\"Model name 'voidful/albert_chinese_large' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'voidful/albert_chinese_large' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'voidful/albert_chinese_small': (\"Model name 'voidful/albert_chinese_small' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'voidful/albert_chinese_small' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'voidful/albert_chinese_tiny': (\"Model name 'voidful/albert_chinese_tiny' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'voidful/albert_chinese_tiny' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'voidful/albert_chinese_xlarge': (\"Model name 'voidful/albert_chinese_xlarge' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'voidful/albert_chinese_xlarge' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'voidful/albert_chinese_xxlarge': (\"Model name 'voidful/albert_chinese_xxlarge' was not found in tokenizers model name list (albert-base-v1, albert-large-v1, albert-xlarge-v1, albert-xxlarge-v1, albert-base-v2, albert-large-v2, albert-xlarge-v2, albert-xxlarge-v2). We assumed 'voidful/albert_chinese_xxlarge' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.\",),\r\n 'wptoux/albert-chinese-large-qa': ('not a string',)}\r\n```", "For reference #3359", "Yes thanks for linking this @patrickvonplaten (I intended to look for this as well)\r\n\r\nThe model pages for those models should already display a (more or less) descriptive message (e.g. https://huggingface.co/djstrong/bg_cs_pl_ru_cased_L-12_H-768_A-12) so I believe we can close this.", "the problem of denpa92/bert-base-cantonese is not solved.", "Is there some way for us to, like, change the config file and make a pull request? I'm not 100% sure how to find the Adam Lin that added ClinicalBert_all_notes and ask him to change it himself...", "> Is there some way for us to, like, change the config file and make a pull request? I'm not 100% sure how to find the Adam Lin that added ClinicalBert_all_notes and ask him to change it himself...\r\n\r\nI think we would like to enable pull requests on model repositories (cc @julien-c)", "Great to hear, @patrickvonplaten. And sorry for the naive question, but where would I find these repos? I've tried searching around a bit for ClinicalBert_all_notes and I've yet to find it on GitHub...", "@drussellmrichie, on the model hub :) https://huggingface.co/models" ]

[]

[ { "login": "patrickvonplaten", "id": 23423619, "node_id": "MDQ6VXNlcjIzNDIzNjE5", "avatar_url": "https://avatars.githubusercontent.com/u/23423619?v=4", "gravatar_id": "", "url": "https://api.github.com/users/patrickvonplaten", "html_url": "https://github.com/patrickvonplaten", "followers_url": "https://api.github.com/users/patrickvonplaten/followers", "following_url": "https://api.github.com/users/patrickvonplaten/following{/other_user}", "gists_url": "https://api.github.com/users/patrickvonplaten/gists{/gist_id}", "starred_url": "https://api.github.com/users/patrickvonplaten/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/patrickvonplaten/subscriptions", "organizations_url": "https://api.github.com/users/patrickvonplaten/orgs", "repos_url": "https://api.github.com/users/patrickvonplaten/repos", "events_url": "https://api.github.com/users/patrickvonplaten/events{/privacy}", "received_events_url": "https://api.github.com/users/patrickvonplaten/received_events", "type": "User", "site_admin": false } ]

[ "Can reproduce :-) Opened a PR to fix it - thanks for the issue @sshearing !" ]

[]

[]

[ "Hi! Thanks for opening this issue. This should have been fixed by https://github.com/huggingface/transformers/pull/5414." ]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5472?src=pr&el=h1) Report\n> Merging [#5472](https://codecov.io/gh/huggingface/transformers/pull/5472?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/306f1a269504b781f886d75105acabf8ae95bd11&el=desc) will **decrease** coverage by `1.08%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5472?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5472 +/- ##\n==========================================\n- Coverage 77.86% 76.77% -1.09% \n==========================================\n Files 141 141 \n Lines 24608 24608 \n==========================================\n- Hits 19160 18892 -268 \n- Misses 5448 5716 +268 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5472?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/data/processors/glue.py](https://codecov.io/gh/huggingface/transformers/pull/5472/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvZ2x1ZS5weQ==) | `49.09% <ø> (ø)` | |\n| [src/transformers/modeling\\_tf\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/5472/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `23.62% <0.00%> (-73.11%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5472/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `26.92% <0.00%> (-68.47%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5472/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.43% <0.00%> (ø)` | |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5472/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `81.09% <0.00%> (+1.37%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/5472/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `98.37% <0.00%> (+25.00%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5472/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `94.98% <0.00%> (+74.19%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5472?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5472?src=pr&el=footer). Last update [306f1a2...5f25ea3](https://codecov.io/gh/huggingface/transformers/pull/5472?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5471?src=pr&el=h1) Report\n> Merging [#5471](https://codecov.io/gh/huggingface/transformers/pull/5471?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/13a8588f2d70fe78dc36d84829c04fa9d39572d1&el=desc) will **increase** coverage by `1.14%`.\n> The diff coverage is `100.00%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5471?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5471 +/- ##\n==========================================\n+ Coverage 76.77% 77.92% +1.14% \n==========================================\n Files 141 141 \n Lines 24617 24617 \n==========================================\n+ Hits 18900 19183 +283 \n+ Misses 5717 5434 -283 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5471?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5471/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19lbGVjdHJhLnB5) | `80.62% <100.00%> (ø)` | |\n| [src/transformers/modeling\\_tf\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5471/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9yb2JlcnRhLnB5) | `43.47% <0.00%> (-49.57%)` | :arrow_down: |\n| [src/transformers/tokenization\\_xlm\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5471/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxtX3JvYmVydGEucHk=) | `61.90% <0.00%> (-33.34%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5471/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.43% <0.00%> (ø)` | |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/5471/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `94.21% <0.00%> (+1.32%)` | :arrow_up: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5471/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `81.09% <0.00%> (+1.37%)` | :arrow_up: |\n| [src/transformers/tokenization\\_transfo\\_xl.py](https://codecov.io/gh/huggingface/transformers/pull/5471/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdHJhbnNmb194bC5weQ==) | `42.48% <0.00%> (+8.92%)` | :arrow_up: |\n| [src/transformers/tokenization\\_xlm.py](https://codecov.io/gh/huggingface/transformers/pull/5471/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxtLnB5) | `82.93% <0.00%> (+66.66%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5471/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `94.98% <0.00%> (+74.19%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5471?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5471?src=pr&el=footer). Last update [13a8588...42044b4](https://codecov.io/gh/huggingface/transformers/pull/5471?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[]

[]

[ "Hi! The SQuAD example doesn't have trainer support yet. We're in the process of adding it. You can see the supported tasks [here](https://github.com/huggingface/transformers/tree/master/examples#the-big-table-of-tasks), only the tasks with Trainer, TFTrainer or pytorch-lightning support can run on TPU." ]

[]

[]

[]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5468?src=pr&el=h1) Report\n> Merging [#5468](https://codecov.io/gh/huggingface/transformers/pull/5468?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/5a0dac53bfd6e69ae64fb3119d607445e1a308d8&el=desc) will **increase** coverage by `0.34%`.\n> The diff coverage is `93.30%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5468?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5468 +/- ##\n==========================================\n+ Coverage 79.33% 79.67% +0.34% \n==========================================\n Files 146 146 \n Lines 26611 26582 -29 \n==========================================\n+ Hits 21111 21180 +69 \n+ Misses 5500 5402 -98 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5468?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/trainer\\_tf.py](https://codecov.io/gh/huggingface/transformers/pull/5468/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyX3RmLnB5) | `12.50% <0.00%> (-0.60%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_flaubert.py](https://codecov.io/gh/huggingface/transformers/pull/5468/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9mbGF1YmVydC5weQ==) | `24.22% <16.66%> (-63.98%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5468/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.97% <71.42%> (-1.85%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/5468/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `71.87% <88.23%> (+0.22%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/5468/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9hbGJlcnQucHk=) | `76.73% <89.28%> (+0.26%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/5468/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl94bG5ldC5weQ==) | `91.34% <95.83%> (-0.05%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/5468/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `96.75% <96.15%> (-0.03%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/5468/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `96.93% <100.00%> (-0.05%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_ctrl.py](https://codecov.io/gh/huggingface/transformers/pull/5468/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9jdHJsLnB5) | `97.84% <100.00%> (-0.01%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5468/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `98.78% <100.00%> (+34.60%)` | :arrow_up: |\n| ... and [20 more](https://codecov.io/gh/huggingface/transformers/pull/5468/diff?src=pr&el=tree-more) | |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5468?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5468?src=pr&el=footer). Last update [5a0dac5...69ea0de](https://codecov.io/gh/huggingface/transformers/pull/5468?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n", "Sure! Will try to find a proper test for that.", "Awesome! Fearing many merge conflicts with https://github.com/huggingface/transformers/pull/5395#pullrequestreview-442374095 :D ", "I fear the same! We should wait to merge #5395 before to merge this one.", "CirlceCi gives the following message error `Too long with no output (exceeded 10m0s): context deadline exceeded` does it means that the tests takes too long now?", "oof yeah, that's what it means! Do you have any idea of how long the added tests take in your local environment, compared to the full test suite?", "I get around 1.5 min per new test / per model => 3min per model => ~33min but this is on my laptop which is really cheap", "That's a slow test :) We can mark them as slow for now (using the `@slow` decorator) and monitor how long they take. If they take too long, we'll have to think of a different way to test those.", "Ok good to me", "Still have to do some bugfix and once all the models pass the tests I will put the `@slow` decorator.", "Ok, now all the models can be saved in TF saved model format. I put some tests to be sure of that, but they have the `@slow` decorator.\r\n\r\nThis is good to merge to me. Nevertheless, I have done several changes in the input of several layers, @LysandreJik can you check if you are ok with that?\r\n\r\nBasically, saved models cannot be run with `list / tuple` inputs, because this is very Python specific and cannot be translated into gRPC.", "@jplu Thanks for your work first! The transformers-based model now can be served by Tensorflow Serving. But I still have one question about max_seg_length. \r\nIn order to make inference faster, is it possible to set max_length to be None? In tf 1.x, I can use the following codes to make serving accept dynamic max_seq_length.\r\n```python\r\nestimator = ...\r\n\r\ndef serving_input_receiver_fn(max_seq_len):\r\n input_ids = tf.compat.v1.placeholder(shape=[None, max_seq_len], dtype=tf.int32, name='input_ids')\r\n input_mask = tf.compat.v1.placeholder(shape=[None, max_seq_len], dtype=tf.int32, name='input_mask')\r\n segment_ids = tf.compat.v1.placeholder(shape=[None, max_seq_len], dtype=tf.int32, name='segment_ids')\r\n features = {'input_ids': input_ids, 'input_mask': input_mask, 'segment_ids': segment_ids}\r\n return tf.estimator.export.build_raw_serving_input_receiver_fn(features)\r\n\r\nestimator.export_savedmodel(model_output_dir, serving_input_receiver_fn(None))\r\n```\r\nI found following codes work in TF2.x. Just ignore this message.\r\n```python\r\ninput_feature = {\r\n 'input_ids': tf.TensorSpec(shape=(None, None), dtype=tf.int32, name='input_ids'),\r\n 'token_type_ids': tf.TensorSpec(shape=(None, None), dtype=tf.int32, name='token_type_ids'),\r\n 'attention_mask': tf.TensorSpec(shape=(None, None), dtype=tf.int32, name='attention_mask')\r\n}\r\nmodel._set_save_spec(input_feature)\r\n```\r\n", "Hello! Thanks for you suggestion. The saved model creation is postponed, and will be for a next PR. This one is here for bugfix only.\n\nYour code will work fine, but not for all the models and tasks. For example token classification uses a different shape, and DistilBert doesn't have a token_type_ids. Unfortunately, it is a bit more complicated than just putting this piece of code somewhere, it has to be task and model independant.", "@jplu What are the issues in deleting `cast_bool_to_primitive` altogether?", "T5 will not work anymore because the number of output depends on the use_cache parameter. And for now we still want to keep a variable length output.\r\n\r\nWe are currently reworking the outputs approach of all the models the output dictionaries instead of tuples. I will come back on this issue of boolean tensor once this new type of output will be available.", "Indeed, I think this is fine, mostly because I expect people to hack around the hidden layers mostly for the PyTorch implementations.\r\n\r\nGood for me!", "This is a valuable point indeed @LysandreJik! Nevertheless, unpacking data is not compliant with TensorFlow Autograph as far as I know, basically we loose this usage as it was before.", "Alright, sounds good! Could you resolve the merge conflict and then we merge?", "Fixed!" ]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5467?src=pr&el=h1) Report\n> Merging [#5467](https://codecov.io/gh/huggingface/transformers/pull/5467?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/35befd9ce31c23a774fd34f57bc44033ce70141d&el=desc) will **decrease** coverage by `0.08%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5467?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5467 +/- ##\n==========================================\n- Coverage 77.57% 77.48% -0.09% \n==========================================\n Files 141 141 \n Lines 24581 24581 \n==========================================\n- Hits 19068 19046 -22 \n- Misses 5513 5535 +22 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5467?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/tokenization\\_xlm\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5467/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxtX3JvYmVydGEucHk=) | `61.90% <0.00%> (-33.34%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5467/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `85.42% <0.00%> (+1.50%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5467?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5467?src=pr&el=footer). Last update [35befd9...80529fa](https://codecov.io/gh/huggingface/transformers/pull/5467?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[]

[]

[]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5465?src=pr&el=h1) Report\n> Merging [#5465](https://codecov.io/gh/huggingface/transformers/pull/5465?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6726416e4a9780e7a92b5681e1446f15f7ef83d3&el=desc) will **decrease** coverage by `0.12%`.\n> The diff coverage is `85.71%`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5465?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5465 +/- ##\n==========================================\n- Coverage 77.52% 77.40% -0.13% \n==========================================\n Files 141 141 \n Lines 24610 24617 +7 \n==========================================\n- Hits 19079 19054 -25 \n- Misses 5531 5563 +32 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5465?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/pipelines.py](https://codecov.io/gh/huggingface/transformers/pull/5465/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9waXBlbGluZXMucHk=) | `76.00% <85.71%> (+0.11%)` | :arrow_up: |\n| [src/transformers/tokenization\\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/5465/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYWxiZXJ0LnB5) | `28.84% <0.00%> (-58.66%)` | :arrow_down: |\n| [src/transformers/generation\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5465/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3V0aWxzLnB5) | `96.82% <0.00%> (-0.29%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5465/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `79.59% <0.00%> (+0.33%)` | :arrow_up: |\n| [src/transformers/configuration\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5465/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3V0aWxzLnB5) | `96.40% <0.00%> (+0.71%)` | :arrow_up: |\n| [src/transformers/tokenization\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/5465/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYXV0by5weQ==) | `97.77% <0.00%> (+2.22%)` | :arrow_up: |\n| [src/transformers/tokenization\\_xlm\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5465/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxtX3JvYmVydGEucHk=) | `95.23% <0.00%> (+33.33%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5465?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5465?src=pr&el=footer). Last update [6726416...25f8c86](https://codecov.io/gh/huggingface/transformers/pull/5465?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[ { "id": 1838412367, "node_id": "MDU6TGFiZWwxODM4NDEyMzY3", "url": "https://api.github.com/repos/huggingface/transformers/labels/model%20card", "name": "model card", "color": "92d5f4", "default": false, "description": "Related to pretrained model cards" } ]

[]

[]

[]

[]

[ "Hello! That's because the user that uploaded that model didn't upload a TensorFlow version, only a PyTorch version. You can see it when you click on \"show all files\", you'll see that there is a `pytorch_model.bin`, but no `tf_model.h5`.\r\n\r\nHere you can solve this by telling the TF model that you want to load from pytorch weights:\r\n\r\n```py\r\nimport tensorflow as tf\r\nPRE_TRAINED_MODEL_NAME = 'ipuneetrathore/bert-base-cased-finetuned-finBERT'\r\nmodel = TFBertForSequenceClassification.from_pretrained(PRE_TRAINED_MODEL_NAME, from_pt=True) # <-- here\r\n```", "and you could also ask the author (I believe @ipuneetrathore) if they could upload a TF version of the weights", "hi @julien-c just wondering if there are any difference if the pytorch weights could be loaded through TF model anyway?", "Just that the PyTorch weights will have to be converted on the fly every time you instantiate your TF model" ]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5462?src=pr&el=h1) Report\n> Merging [#5462](https://codecov.io/gh/huggingface/transformers/pull/5462?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/35befd9ce31c23a774fd34f57bc44033ce70141d&el=desc) will **decrease** coverage by `0.93%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5462?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5462 +/- ##\n==========================================\n- Coverage 77.57% 76.63% -0.94% \n==========================================\n Files 141 141 \n Lines 24581 24581 \n==========================================\n- Hits 19068 18838 -230 \n- Misses 5513 5743 +230 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5462?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/5462/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `23.62% <0.00%> (-73.11%)` | :arrow_down: |\n| [src/transformers/tokenization\\_marian.py](https://codecov.io/gh/huggingface/transformers/pull/5462/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fbWFyaWFuLnB5) | `68.14% <0.00%> (-25.67%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5462/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `79.26% <0.00%> (-0.34%)` | :arrow_down: |\n| [src/transformers/configuration\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5462/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9jb25maWd1cmF0aW9uX3V0aWxzLnB5) | `96.40% <0.00%> (+0.71%)` | :arrow_up: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5462/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `81.09% <0.00%> (+1.37%)` | :arrow_up: |\n| [src/transformers/tokenization\\_auto.py](https://codecov.io/gh/huggingface/transformers/pull/5462/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fYXV0by5weQ==) | `97.77% <0.00%> (+2.22%)` | :arrow_up: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5462/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.68% <0.00%> (+2.76%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5462/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `94.98% <0.00%> (+74.19%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5462?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5462?src=pr&el=footer). Last update [35befd9...89278a5](https://codecov.io/gh/huggingface/transformers/pull/5462?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[]

[]

[ "I'm not sure I completely understand your process. You're loading a Reformer model - which one, with which checkpoint?\r\n\r\nYou want to use another tokenizer. Which one, loaded from which checkpoint?", "I am using this notebook: https://github.com/patrickvonplaten/notebooks/blob/master/Reformer_For_Masked_LM.ipynb\r\nThe tokenizer I am using is the t5-large from the modelhub.\r\n\r\nRestarting my complete System solved the problem, seems like there was an error with cuda or the anaconda enviroment" ]

[]

[]

[ "I can reproduce! Thank you for opening an issue, I'm looking into it now.", "Same error (StackOverflow--> https://stackoverflow.com/questions/67004233/typeerror-zeros-like-argument-input-when-fine-tuning-on-mlm) what was the fix in the end @LysandreJik ?", "@LysandreJik Is there any way to fix this (for what I presume is a model pretrained on the old HuggingFace version)?", "Sorry just seeing this now - @neel04 are you still facing the issue? @msamogh can you open a new issue and fill in the issue template (with full error, environment, code run)? Thanks", "I don't really remember what I was trying to do :sweat_smile: Sorry, couldn't help you more. I think the problem was some changes in the API, while the example notebooks weren't updated at that time - so the `max_length` argument (which took `int`) didn't work leading to that error. Now, its changed to a `str` whic represents padding strategy - and since it works now with my current problem, I personally don't think the issue remains anymore :hugs: \r\n\r\nI haven't done the training though, so I would surely update you if I encouter it again!\r\n\r\n**EDIT:** My training works (albeit with small batch size), so you must have processed your data wrongly @msamogh. Check out the updated example notebooks to get an idea on how to build your datasets with the :hugs: `Datasets` lib" ]

[]

[]

[ "Hi! The way to save the transformers model is using the `save_pretrained` method, which saves both the configuration and the model as an h5 file. Can you try using it instead?", "> Hi! The way to save the transformers model is using the `save_pretrained` method, which saves both the configuration and the model as an h5 file. Can you try using it instead?\r\n\r\nI am not saving the \"transformers model\" instead use it as a top layer of a Keras model. Then error occurs when saving the model that includes the \"transformers model.\"", "Ok, maybe @jplu or @patrickvonplaten can have a look when they have some bandwidth.", "As a first glance, I can say that it is \"normal\" because the `DistilBert` model has a config parameter, which doesn't make it compliant with sequential models. Create a subclass model instead to see if it works.\r\n\r\nBut this is just a quick guess, I will check it deeper when have some time.", "I found that, model could be save in tensorflow saved_model using: \r\n`tf.saved_model.save(model, './models/model')`\r\n\r\nHowever, I was not able to save in Keras .h5 format. That's fine for me now. So, I close this issue. " ]

[]

[ { "login": "sshleifer", "id": 6045025, "node_id": "MDQ6VXNlcjYwNDUwMjU=", "avatar_url": "https://avatars.githubusercontent.com/u/6045025?v=4", "gravatar_id": "", "url": "https://api.github.com/users/sshleifer", "html_url": "https://github.com/sshleifer", "followers_url": "https://api.github.com/users/sshleifer/followers", "following_url": "https://api.github.com/users/sshleifer/following{/other_user}", "gists_url": "https://api.github.com/users/sshleifer/gists{/gist_id}", "starred_url": "https://api.github.com/users/sshleifer/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/sshleifer/subscriptions", "organizations_url": "https://api.github.com/users/sshleifer/orgs", "repos_url": "https://api.github.com/users/sshleifer/repos", "events_url": "https://api.github.com/users/sshleifer/events{/privacy}", "received_events_url": "https://api.github.com/users/sshleifer/received_events", "type": "User", "site_admin": false } ]

[ "Ha, I didn't know the Tokenizer between Bart and mBart is different. I just noticed there is a class `MBartTokenizer`.\r\n\r\nIt seems like this class is not documented on [HuggingFace documentation](https://huggingface.co/transformers/model_doc/bart.html). Maybe we should consider adding it ?\r\n\r\n_Also the model card for `sshleifer/mbart-large-cc25` may need an update_\r\n\r\n---\r\n\r\nAlso, the following is still not working :\r\n\r\n```python\r\nfrom transformers import MBartTokenizer\r\n\r\ntokenizer = MBartTokenizer.from_pretrained(\"sshleifer/mbart-large-cc25\")\r\n```\r\n\r\nOnly `tokenizer = MBartTokenizer.from_pretrained('facebook/mbart-large-en-ro')` seems to work.\r\n\r\n**Can I use Tokenizer from checkpoint `facebook/mbart-large-en-ro` for the model `sshleifer/mbart-large-cc25` ?**", "mbart-large-cc25 does not work well yet, the PR is still open #3513.\r\nNonetheless these are all things I should fix, thanks!", "For your second question, no. At the moment that tokenizer will not work well. Do you have fairseq cc25 working well?\r\n\r\n**Update:** just moved it to `facebook/mbart-large-cc25`. AutoTokenizer should work. ", "I didn't try the fairseq model, went directly for HF implementation ^^" ]

[]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5457?src=pr&el=h1) Report\n> Merging [#5457](https://codecov.io/gh/huggingface/transformers/pull/5457?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/306f1a269504b781f886d75105acabf8ae95bd11&el=desc) will **decrease** coverage by `0.28%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5457?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5457 +/- ##\n==========================================\n- Coverage 77.86% 77.57% -0.29% \n==========================================\n Files 141 141 \n Lines 24608 24608 \n==========================================\n- Hits 19160 19089 -71 \n- Misses 5448 5519 +71 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5457?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/tokenization\\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/5457/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxuZXQucHk=) | `32.43% <0.00%> (-55.86%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_distilbert.py](https://codecov.io/gh/huggingface/transformers/pull/5457/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9kaXN0aWxiZXJ0LnB5) | `66.25% <0.00%> (-32.52%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5457/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.18% <0.00%> (-0.26%)` | :arrow_down: |\n| [src/transformers/file\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5457/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `79.59% <0.00%> (+0.33%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/5457/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `98.37% <0.00%> (+25.00%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5457?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5457?src=pr&el=footer). Last update [306f1a2...e08f8b7](https://codecov.io/gh/huggingface/transformers/pull/5457?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[ { "id": 1838412367, "node_id": "MDU6TGFiZWwxODM4NDEyMzY3", "url": "https://api.github.com/repos/huggingface/transformers/labels/model%20card", "name": "model card", "color": "92d5f4", "default": false, "description": "Related to pretrained model cards" } ]

[]

[ "# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5456?src=pr&el=h1) Report\n> Merging [#5456](https://codecov.io/gh/huggingface/transformers/pull/5456?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/306f1a269504b781f886d75105acabf8ae95bd11&el=desc) will **decrease** coverage by `1.05%`.\n> The diff coverage is `n/a`.\n\n[](https://codecov.io/gh/huggingface/transformers/pull/5456?src=pr&el=tree)\n\n```diff\n@@ Coverage Diff @@\n## master #5456 +/- ##\n==========================================\n- Coverage 77.86% 76.80% -1.06% \n==========================================\n Files 141 141 \n Lines 24608 24608 \n==========================================\n- Hits 19160 18901 -259 \n- Misses 5448 5707 +259 \n```\n\n\n| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5456?src=pr&el=tree) | Coverage Δ | |\n|---|---|---|\n| [src/transformers/modeling\\_tf\\_mobilebert.py](https://codecov.io/gh/huggingface/transformers/pull/5456/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9tb2JpbGViZXJ0LnB5) | `23.62% <0.00%> (-73.11%)` | :arrow_down: |\n| [src/transformers/tokenization\\_xlm\\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5456/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxtX3JvYmVydGEucHk=) | `61.90% <0.00%> (-33.34%)` | :arrow_down: |\n| [src/transformers/modeling\\_tf\\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/5456/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `65.69% <0.00%> (-29.45%)` | :arrow_down: |\n| [src/transformers/tokenization\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5456/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fb3BlbmFpLnB5) | `70.76% <0.00%> (-13.08%)` | :arrow_down: |\n| [src/transformers/generation\\_tf\\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5456/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `80.15% <0.00%> (-6.29%)` | :arrow_down: |\n| [src/transformers/tokenization\\_utils\\_base.py](https://codecov.io/gh/huggingface/transformers/pull/5456/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25fdXRpbHNfYmFzZS5weQ==) | `92.89% <0.00%> (-1.33%)` | :arrow_down: |\n| [src/transformers/modeling\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5456/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `81.09% <0.00%> (+1.37%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_bert.py](https://codecov.io/gh/huggingface/transformers/pull/5456/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9iZXJ0LnB5) | `98.37% <0.00%> (+25.00%)` | :arrow_up: |\n| [src/transformers/modeling\\_tf\\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5456/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `94.98% <0.00%> (+74.19%)` | :arrow_up: |\n\n------\n\n[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5456?src=pr&el=continue).\n> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)\n> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`\n> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5456?src=pr&el=footer). Last update [306f1a2...8ce649f](https://codecov.io/gh/huggingface/transformers/pull/5456?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).\n" ]

[ { "id": 1834056635, "node_id": "MDU6TGFiZWwxODM0MDU2NjM1", "url": "https://api.github.com/repos/huggingface/transformers/labels/Core:%20Tokenization", "name": "Core: Tokenization", "color": "FF4446", "default": false, "description": "Internals of the library; Tokenization." } ]

[]

[ "Hi @RayLei Have a look at this https://huggingface.co/transformers/preprocessing.html" ]