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@@ -3,7 +3,12 @@ license: mit
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  library_name: dots_ocr
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  pipeline_tag: image-text-to-text
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  tags:
 
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  - ocr
 
 
 
 
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  language:
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  - en
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  - zh
@@ -861,7 +866,7 @@ This is an inhouse benchmark which contain 1493 pdf images with 100 languages.
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  <td>Nanonets OCR</td>
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  <td>67.0</td>
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  <td>68.6</td>
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- <td><strong>77.7</strong></td>
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  <td>39.5</td>
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  <td>40.7</td>
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  <td>69.9</td>
@@ -1026,7 +1031,7 @@ pip install -e .
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  ### Download Model Weights
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  > 💡**Note:** Please use a directory name without periods (e.g., `DotsOCR` instead of `dots.ocr`) for the model save path. This is a temporary workaround pending our integration with Transformers.
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  ```shell
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- python tools/download_model.py
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  ```
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@@ -1037,14 +1042,17 @@ The [Docker Image](https://hub.docker.com/r/rednotehilab/dots.ocr) is based on t
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  ```shell
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  # You need to register model to vllm at first
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- export hf_model_path=./weights/DotsOCR # Path to your downloaded model weights
 
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  export PYTHONPATH=$(dirname "$hf_model_path"):$PYTHONPATH
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  sed -i '/^from vllm\.entrypoints\.cli\.main import main$/a\
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- from DotsOCR import modeling_dots_ocr_vllm' `which vllm`
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  # launch vllm server
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  CUDA_VISIBLE_DEVICES=0 vllm serve ${hf_model_path} --tensor-parallel-size 1 --gpu-memory-utilization 0.95 --chat-template-content-format string --served-model-name model --trust-remote-code
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  # vllm api demo
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  python3 ./demo/demo_vllm.py --prompt_mode prompt_layout_all_en
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  ```
 
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  library_name: dots_ocr
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  pipeline_tag: image-text-to-text
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  tags:
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+ - image-to-text
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  - ocr
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+ - document-parse
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+ - layout
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+ - table
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+ - formula
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  language:
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  - en
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  - zh
 
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  <td>Nanonets OCR</td>
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  <td>67.0</td>
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  <td>68.6</td>
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+ <td>77.7</td>
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  <td>39.5</td>
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  <td>40.7</td>
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  <td>69.9</td>
 
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  ### Download Model Weights
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  > 💡**Note:** Please use a directory name without periods (e.g., `DotsOCR` instead of `dots.ocr`) for the model save path. This is a temporary workaround pending our integration with Transformers.
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  ```shell
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+ python3 tools/download_model.py
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  ```
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  ```shell
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  # You need to register model to vllm at first
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+ python3 tools/download_model.py
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+ export hf_model_path=./weights/DotsOCR # Path to your downloaded model weights, Please use a directory name without periods (e.g., `DotsOCR` instead of `dots.ocr`) for the model save path. This is a temporary workaround pending our integration with Transformers.
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  export PYTHONPATH=$(dirname "$hf_model_path"):$PYTHONPATH
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  sed -i '/^from vllm\.entrypoints\.cli\.main import main$/a\
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+ from DotsOCR import modeling_dots_ocr_vllm' `which vllm` # If you downloaded model weights by yourself, please replace `DotsOCR` by your model saved directory name, and remember to use a directory name without periods (e.g., `DotsOCR` instead of `dots.ocr`)
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  # launch vllm server
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  CUDA_VISIBLE_DEVICES=0 vllm serve ${hf_model_path} --tensor-parallel-size 1 --gpu-memory-utilization 0.95 --chat-template-content-format string --served-model-name model --trust-remote-code
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+ # If you get a ModuleNotFoundError: No module named 'DotsOCR', please check the note above on the saved model directory name.
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+
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  # vllm api demo
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  python3 ./demo/demo_vllm.py --prompt_mode prompt_layout_all_en
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  ```