Upload 12 files
Browse files- README.md +202 -0
- adapter_config.json +40 -0
- adapter_model.safetensors +3 -0
- added_tokens.json +6 -0
- config.json +31 -0
- rng_state.pth +3 -0
- scheduler.pt +3 -0
- special_tokens_map.json +30 -0
- tokenizer.model +3 -0
- tokenizer_config.json +85 -0
- trainer_state.json +411 -0
- training_args.bin +3 -0
README.md
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---
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base_model: meta-llama/CodeLlama-34b-Python-hf
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library_name: peft
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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### Framework versions
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- PEFT 0.14.0
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "meta-llama/CodeLlama-34b-Python-hf",
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"bias": "none",
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": null,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 16,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": [
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"embed_tokens",
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"lm_head"
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],
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"peft_type": "LORA",
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"r": 4,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"v_proj",
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"q_proj",
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"down_proj",
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"gate_proj",
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"up_proj",
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"o_proj",
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"k_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:b326aef5de7bfa01b661c785355ee93016a39a14e97eac3f0303664585b538cf
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size 3255131824
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added_tokens.json
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{
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"▁<EOT>": 32003,
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"▁<MID>": 32001,
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"▁<PRE>": 32000,
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"▁<SUF>": 32002
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}
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config.json
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{
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"_attn_implementation_autoset": true,
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"_name_or_path": "meta-llama/CodeLlama-34b-Python-hf",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 8192,
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"initializer_range": 0.02,
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"intermediate_size": 22016,
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"max_position_embeddings": 16384,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 64,
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"num_hidden_layers": 48,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 1000000,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.46.3",
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"use_cache": false,
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"vocab_size": 32004
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}
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rng_state.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:53f2b74eaf93a795d5de1067c54c8349da01a06675017515bfdb202b1ca8d59b
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size 14244
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scheduler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:df0525beb609beb82cb3bd53cd40bda1ec6121fa958580c4a0a93cad634d9288
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size 1064
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special_tokens_map.json
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{
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"additional_special_tokens": [
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"▁<PRE>",
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"▁<MID>",
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"▁<SUF>",
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"▁<EOT>"
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],
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "</s>",
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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size 499723
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tokenizer_config.json
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"content": "▁<EOT>",
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"▁<EOT>"
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"eot_token": "▁<EOT>",
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