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README.md

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+---
+pipeline_tag: image-text-to-text
+language:
+- multilingual
+tags:
+- got
+- vision-language
+- ocr2.0
+- custom_code
+license: apache-2.0
+---
+
+## Same model as located at [stepfun-ai/GOT-OCR2_0](https://huggingface.co/stepfun-ai/GOT-OCR2_0) with customized source code that:
+1) Removes the `verovio` dependency since most people don't need to OCR musical annotation.
+2) Allows a user to use `float16` if their GPU doesn't support `bfloat`.
+3) Updated to support `Transformers==4.48.3` so it no longer gives a bunch of warning messages.
+
+<details><summary>ORIGINAL MODEL CARD HERE</summary>
+
+
+<h1>General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model
+</h1>
+
+[🔋Online Demo](https://huggingface.co/spaces/ucaslcl/GOT_online) | [🌟GitHub](https://github.com/Ucas-HaoranWei/GOT-OCR2.0/) | [📜Paper](https://arxiv.org/abs/2409.01704)</a> 
+
+
+[Haoran Wei*](https://scholar.google.com/citations?user=J4naK0MAAAAJ&hl=en), Chenglong Liu*, Jinyue Chen, Jia Wang, Lingyu Kong, Yanming Xu,  [Zheng Ge](https://joker316701882.github.io/), Liang Zhao, [Jianjian Sun](https://scholar.google.com/citations?user=MVZrGkYAAAAJ&hl=en), [Yuang Peng](https://scholar.google.com.hk/citations?user=J0ko04IAAAAJ&hl=zh-CN&oi=ao), Chunrui Han, [Xiangyu Zhang](https://scholar.google.com/citations?user=yuB-cfoAAAAJ&hl=en)
+
+
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6653eee7a2d7a882a805ab95/QCEFY-M_YG3Bp5fn1GQ8X.jpeg)
+
+
+
+## Usage
+Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.10：
+```
+torch==2.0.1
+torchvision==0.15.2
+transformers==4.37.2
+tiktoken==0.6.0
+verovio==4.3.1
+accelerate==0.28.0
+```
+
+
+```python
+from transformers import AutoModel, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained('ucaslcl/GOT-OCR2_0', trust_remote_code=True)
+model = AutoModel.from_pretrained('ucaslcl/GOT-OCR2_0', trust_remote_code=True, low_cpu_mem_usage=True, device_map='cuda', use_safetensors=True, pad_token_id=tokenizer.eos_token_id)
+model = model.eval().cuda()
+
+
+# input your test image
+image_file = 'xxx.jpg'
+
+# plain texts OCR
+res = model.chat(tokenizer, image_file, ocr_type='ocr')
+
+# format texts OCR:
+# res = model.chat(tokenizer, image_file, ocr_type='format')
+
+# fine-grained OCR:
+# res = model.chat(tokenizer, image_file, ocr_type='ocr', ocr_box='')
+# res = model.chat(tokenizer, image_file, ocr_type='format', ocr_box='')
+# res = model.chat(tokenizer, image_file, ocr_type='ocr', ocr_color='')
+# res = model.chat(tokenizer, image_file, ocr_type='format', ocr_color='')
+
+# multi-crop OCR:
+# res = model.chat_crop(tokenizer, image_file, ocr_type='ocr')
+# res = model.chat_crop(tokenizer, image_file, ocr_type='format')
+
+# render the formatted OCR results:
+# res = model.chat(tokenizer, image_file, ocr_type='format', render=True, save_render_file = './demo.html')
+
+print(res)
+
+
+```
+More details about 'ocr_type', 'ocr_box', 'ocr_color', and 'render' can be found at our GitHub.
+Our training codes are available at our [GitHub](https://github.com/Ucas-HaoranWei/GOT-OCR2.0/).
+
+
+
+## More Multimodal Projects
+
+👏 Welcome to explore more multimodal projects of our team:
+
+[Vary](https://github.com/Ucas-HaoranWei/Vary) | [Fox](https://github.com/ucaslcl/Fox) | [OneChart](https://github.com/LingyvKong/OneChart)
+
+## Citation
+
+If you find our work helpful, please consider citing our papers 📝 and liking this project ❤️！
+
+```bib
+@article{wei2024general,
+  title={General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model},
+  author={Wei, Haoran and Liu, Chenglong and Chen, Jinyue and Wang, Jia and Kong, Lingyu and Xu, Yanming and Ge, Zheng and Zhao, Liang and Sun, Jianjian and Peng, Yuang and others},
+  journal={arXiv preprint arXiv:2409.01704},
+  year={2024}
+}
+@article{liu2024focus,
+  title={Focus Anywhere for Fine-grained Multi-page Document Understanding},
+  author={Liu, Chenglong and Wei, Haoran and Chen, Jinyue and Kong, Lingyu and Ge, Zheng and Zhu, Zining and Zhao, Liang and Sun, Jianjian and Han, Chunrui and Zhang, Xiangyu},
+  journal={arXiv preprint arXiv:2405.14295},
+  year={2024}
+}
+@article{wei2023vary,
+  title={Vary: Scaling up the Vision Vocabulary for Large Vision-Language Models},
+  author={Wei, Haoran and Kong, Lingyu and Chen, Jinyue and Zhao, Liang and Ge, Zheng and Yang, Jinrong and Sun, Jianjian and Han, Chunrui and Zhang, Xiangyu},
+  journal={arXiv preprint arXiv:2312.06109},
+  year={2023}
+}
+```
+
+</details>