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models/MFR/UniMERNet/README.md

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+---
+license: apache-2.0
+---
+UniMERNet: A Universal Network for Mathematical Expression Recognition in Real-World Scenarios. 
+
+Visit our GitHub repository at [unimernet](https://github.com/opendatalab/unimernet) for more information. 

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models/MFR/unimernet_base/.mv

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+Revision:master,CreatedAt:1725608506

models/MFR/unimernet_base/README.md

@@ -0,0 +1,48 @@
+---
+license: apache-2.0
+---
+## UniMERNet: A Universal Network for Mathematical Expression Recognition in Real-World Scenarios. 
+
+Visit our GitHub repository at [UniMERNet](https://github.com/opendatalab/unimernet) for more information. 
+
+
+## 引用
+```
+@misc{wang2024unimernetuniversalnetworkrealworld,
+      title={UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition}, 
+      author={Bin Wang and Zhuangcheng Gu and Guang Liang and Chao Xu and Bo Zhang and Botian Shi and Conghui He},
+      year={2024},
+      eprint={2404.15254},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2404.15254}, 
+}
+
+@misc{wang2024cdmreliablemetricfair,
+      title={CDM: A Reliable Metric for Fair and Accurate Formula Recognition Evaluation}, 
+      author={Bin Wang and Fan Wu and Linke Ouyang and Zhuangcheng Gu and Rui Zhang and Renqiu Xia and Bo Zhang and Conghui He},
+      year={2024},
+      eprint={2409.03643},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2409.03643}, 
+}
+
+@misc{he2024opendatalabempoweringgeneralartificial,
+      title={OpenDataLab: Empowering General Artificial Intelligence with Open Datasets}, 
+      author={Conghui He and Wei Li and Zhenjiang Jin and Chao Xu and Bin Wang and Dahua Lin},
+      year={2024},
+      eprint={2407.13773},
+      archivePrefix={arXiv},
+      primaryClass={cs.DL},
+      url={https://arxiv.org/abs/2407.13773}, 
+}
+```
+```
+
+## MD5 checksums
+```
+97f4867b4ff4e9a96c8daba8aaa793b4  tokenizer_config.json
+351652071425d3d36a634ccc8efb22e8  tokenizer.json
+ff4391872dad6688f21ed140009d817b  pytorch_model.pth
+```

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models/MFR/unimernet_base/configuration.json

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+{"framework":"Pytorch","task":"ocr-recognition"}

models/MFR/unimernet_base/preprocessor_config.json

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+    672
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+  "train": false
+}

models/MFR/unimernet_base/pytorch_model.pth

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models/MFR/unimernet_base/unimernet_base.yaml

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+model:
+  arch: unimernet
+  model_type: unimernet
+  model_config:
+    model_name: ./models/unimernet_base
+    max_seq_len: 1536
+
+  load_pretrained: True
+  pretrained: './models/unimernet_base/pytorch_model.pth'
+  tokenizer_config:
+    path: ./models/unimernet_base
+
+datasets:
+  formula_rec_eval:
+    vis_processor:
+      eval:
+        name: "formula_image_eval"
+        image_size:
+          - 192
+          - 672
+   
+run:
+  runner: runner_iter
+  task: unimernet_train
+
+  batch_size_train: 64
+  batch_size_eval: 64
+  num_workers: 1
+
+  iters_per_inner_epoch: 2000
+  max_iters: 60000
+
+  seed: 42
+  output_dir: "../output/demo"
+
+  evaluate: True
+  test_splits: [ "eval" ]
+
+  device: "cuda"
+  world_size: 1
+  dist_url: "env://"
+  distributed: True
+  distributed_type: ddp  # or fsdp when train llm
+
+  generate_cfg:
+    temperature: 0.0

models/MFR/unimernet_small/.mv

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+Revision:master,CreatedAt:1725608428

models/MFR/unimernet_small/README.md

@@ -0,0 +1,47 @@
+---
+license: apache-2.0
+---
+## UniMERNet: A Universal Network for Mathematical Expression Recognition in Real-World Scenarios. 
+
+Visit our GitHub repository at [UniMERNet](https://github.com/opendatalab/unimernet) for more information. 
+
+
+## 引用
+```
+@misc{wang2024unimernetuniversalnetworkrealworld,
+      title={UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition}, 
+      author={Bin Wang and Zhuangcheng Gu and Guang Liang and Chao Xu and Bo Zhang and Botian Shi and Conghui He},
+      year={2024},
+      eprint={2404.15254},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2404.15254}, 
+}
+
+@misc{wang2024cdmreliablemetricfair,
+      title={CDM: A Reliable Metric for Fair and Accurate Formula Recognition Evaluation}, 
+      author={Bin Wang and Fan Wu and Linke Ouyang and Zhuangcheng Gu and Rui Zhang and Renqiu Xia and Bo Zhang and Conghui He},
+      year={2024},
+      eprint={2409.03643},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2409.03643}, 
+}
+
+@misc{he2024opendatalabempoweringgeneralartificial,
+      title={OpenDataLab: Empowering General Artificial Intelligence with Open Datasets}, 
+      author={Conghui He and Wei Li and Zhenjiang Jin and Chao Xu and Bin Wang and Dahua Lin},
+      year={2024},
+      eprint={2407.13773},
+      archivePrefix={arXiv},
+      primaryClass={cs.DL},
+      url={https://arxiv.org/abs/2407.13773}, 
+}
+```
+
+## MD5 checksums
+```
+97f4867b4ff4e9a96c8daba8aaa793b4  tokenizer_config.json
+351652071425d3d36a634ccc8efb22e8  tokenizer.json
+430e426354e71624fb096c5c7ad90a78  pytorch_model.pth
+```

models/MFR/unimernet_small/config.json

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+}

models/MFR/unimernet_small/configuration.json

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models/MFR/unimernet_small/preprocessor_config.json

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+}

models/MFR/unimernet_small/unimernet_small.yaml

@@ -0,0 +1,46 @@
+model:
+  arch: unimernet
+  model_type: unimernet
+  model_config:
+    model_name: ./models/unimernet_small
+    max_seq_len: 1536
+
+  load_pretrained: True
+  pretrained: './models/unimernet_small/pytorch_model.pth'
+  tokenizer_config:
+    path: ./models/unimernet_small
+
+datasets:
+  formula_rec_eval:
+    vis_processor:
+      eval:
+        name: "formula_image_eval"
+        image_size:
+          - 192
+          - 672
+   
+run:
+  runner: runner_iter
+  task: unimernet_train
+
+  batch_size_train: 64
+  batch_size_eval: 64
+  num_workers: 1
+
+  iters_per_inner_epoch: 2000
+  max_iters: 60000
+
+  seed: 42
+  output_dir: "../output/demo"
+
+  evaluate: True
+  test_splits: [ "eval" ]
+
+  device: "cuda"
+  world_size: 1
+  dist_url: "env://"
+  distributed: True
+  distributed_type: ddp  # or fsdp when train llm
+
+  generate_cfg:
+    temperature: 0.0

models/MFR/unimernet_tiny/.mv

@@ -0,0 +1 @@
+Revision:master,CreatedAt:1725608470

models/MFR/unimernet_tiny/README.md

@@ -0,0 +1,48 @@
+---
+license: apache-2.0
+---
+## UniMERNet: A Universal Network for Mathematical Expression Recognition in Real-World Scenarios. 
+
+Visit our GitHub repository at [UniMERNet](https://github.com/opendatalab/unimernet) for more information. 
+
+
+## 引用
+```
+@misc{wang2024unimernetuniversalnetworkrealworld,
+      title={UniMERNet: A Universal Network for Real-World Mathematical Expression Recognition}, 
+      author={Bin Wang and Zhuangcheng Gu and Guang Liang and Chao Xu and Bo Zhang and Botian Shi and Conghui He},
+      year={2024},
+      eprint={2404.15254},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2404.15254}, 
+}
+
+@misc{wang2024cdmreliablemetricfair,
+      title={CDM: A Reliable Metric for Fair and Accurate Formula Recognition Evaluation}, 
+      author={Bin Wang and Fan Wu and Linke Ouyang and Zhuangcheng Gu and Rui Zhang and Renqiu Xia and Bo Zhang and Conghui He},
+      year={2024},
+      eprint={2409.03643},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2409.03643}, 
+}
+
+@misc{he2024opendatalabempoweringgeneralartificial,
+      title={OpenDataLab: Empowering General Artificial Intelligence with Open Datasets}, 
+      author={Conghui He and Wei Li and Zhenjiang Jin and Chao Xu and Bin Wang and Dahua Lin},
+      year={2024},
+      eprint={2407.13773},
+      archivePrefix={arXiv},
+      primaryClass={cs.DL},
+      url={https://arxiv.org/abs/2407.13773}, 
+}
+```
+```
+
+## MD5 checksums
+```
+97f4867b4ff4e9a96c8daba8aaa793b4  tokenizer_config.json
+351652071425d3d36a634ccc8efb22e8  tokenizer.json
+72b53a2152af43a57f8d5eebf8e31562  pytorch_model.pth
+```

models/MFR/unimernet_tiny/config.json

@@ -0,0 +1,193 @@
+{
+  "_name_or_path": "unimernet/checkpoint-300000",
+  "architectures": [
+    "VisionEncoderDecoderModel"
+  ],
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+      "0": "LABEL_0",
+      "1": "LABEL_1"
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+      420,
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+    "num_beams": 1,
+    "num_channels": 3,
+    "num_heads": [
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+      8,
+      16
+    ],
+    "num_layers": 4,
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+    "output_attentions": false,
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+    "patch_size": 4,
+    "path_norm": true,
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+    "problem_type": null,
+    "pruned_heads": {},
+    "qkv_bias": true,
+    "remove_invalid_values": false,
+    "repetition_penalty": 1.0,
+    "return_dict": true,
+    "return_dict_in_generate": false,
+    "sep_token_id": null,
+    "suppress_tokens": null,
+    "task_specific_params": null,
+    "temperature": 1.0,
+    "tf_legacy_loss": false,
+    "tie_encoder_decoder": false,
+    "tie_word_embeddings": true,
+    "tokenizer_class": null,
+    "top_k": 50,
+    "top_p": 1.0,
+    "torch_dtype": null,
+    "torchscript": false,
+    "typical_p": 1.0,
+    "use_2d_embeddings": false,
+    "use_absolute_embeddings": false,
+    "use_bfloat16": false,
+    "window_size": 5
+  },
+  "is_encoder_decoder": true,
+  "model_type": "vision-encoder-decoder",
+  "pad_token_id": 1,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.36.0"
+}

models/MFR/unimernet_tiny/configuration.json

@@ -0,0 +1 @@
+{"framework":"Pytorch","task":"ocr-recognition"}

models/MFR/unimernet_tiny/preprocessor_config.json

@@ -0,0 +1,36 @@
+{
+  "do_align_long_axis": false,
+  "do_normalize": false,
+  "do_pad": false,
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+  "image_std": [
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+    0.225
+  ],
+  "max_size": {
+    "height": 192,
+    "width": 672
+  },
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+    4
+  ],
+  "processor_class": "VariableDonutProcessor",
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": [
+    192,
+    672
+  ],
+  "train": false
+}

models/MFR/unimernet_tiny/pytorch_model.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6f7608624e2d7549c7f0f05fcfbe073ae521328cf70f1d46374d96f9881d7371
+size 430075701

models/MFR/unimernet_tiny/tokenizer_config.json

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+}

models/MFR/unimernet_tiny/unimernet_tiny.yaml

@@ -0,0 +1,46 @@
+model:
+  arch: unimernet
+  model_type: unimernet
+  model_config:
+    model_name: ./models/unimernet_tiny
+    max_seq_len: 1536
+
+  load_pretrained: True
+  pretrained: './models/unimernet_tiny/pytorch_model.pth'
+  tokenizer_config:
+    path: ./models/unimernet_tiny
+
+datasets:
+  formula_rec_eval:
+    vis_processor:
+      eval:
+        name: "formula_image_eval"
+        image_size:
+          - 192
+          - 672
+   
+run:
+  runner: runner_iter
+  task: unimernet_train
+
+  batch_size_train: 64
+  batch_size_eval: 64
+  num_workers: 1
+
+  iters_per_inner_epoch: 2000
+  max_iters: 60000
+
+  seed: 42
+  output_dir: "../output/demo"
+
+  evaluate: True
+  test_splits: [ "eval" ]
+
+  device: "cuda"
+  world_size: 1
+  dist_url: "env://"
+  distributed: True
+  distributed_type: ddp  # or fsdp when train llm
+
+  generate_cfg:
+    temperature: 0.0

models/README.md

@@ -0,0 +1,29 @@
+Put [model files]() here:
+
+```
+./
+├── Layout
+│   ├── config.json
+│   └── model_final.pth
+├── MFD
+│   └── weights.pt
+├── MFR
+│   └── UniMERNet
+│       ├── config.json
+│       ├── preprocessor_config.json
+│       ├── pytorch_model.bin
+│       ├── README.md
+│       ├── tokenizer_config.json
+│       └── tokenizer.json
+├── TabRec
+│   └── StructEqTable
+│       ├── config.json
+│       ├──generation_config.json
+│       ├──model.safetensors
+│       ├──preprocessor_config.json
+│       ├──special_tokens_map.json
+│       ├──spiece.model
+│       ├──tokenizer_config.json
+│       └──tokenizer.json
+└── README.md
+```

models/TabRec/StructEqTable/config.json

@@ -0,0 +1,36 @@
+{
+  "_name_or_path": "/cpfs01/user/zhouhongbin/code/StructEqTable-deepspeed/ckpt/pretrained/pix2struct-base-zh",
+  "architectures": [
+    "Pix2StructForConditionalGeneration"
+  ],
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "initializer_factor": 1.0,
+  "initializer_range": 0.02,
+  "is_encoder_decoder": true,
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