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aarishshahmohsin
/
got_ocr_2

Image-Text-to-Text
Transformers
Safetensors
multilingual
GOT
feature-extraction
got
vision-language
ocr2.0
custom_code
Model card Files Files and versions
xet
Community

Instructions to use aarishshahmohsin/got_ocr_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use aarishshahmohsin/got_ocr_2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="aarishshahmohsin/got_ocr_2", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("aarishshahmohsin/got_ocr_2", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use aarishshahmohsin/got_ocr_2 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "aarishshahmohsin/got_ocr_2"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "aarishshahmohsin/got_ocr_2",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/aarishshahmohsin/got_ocr_2
  • SGLang

    How to use aarishshahmohsin/got_ocr_2 with SGLang:

    Install from pip and serve model
    # Install SGLang from pip:
    pip install sglang
    # Start the SGLang server:
    python3 -m sglang.launch_server \
        --model-path "aarishshahmohsin/got_ocr_2" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "aarishshahmohsin/got_ocr_2",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker images
    docker run --gpus all \
        --shm-size 32g \
        -p 30000:30000 \
        -v ~/.cache/huggingface:/root/.cache/huggingface \
        --env "HF_TOKEN=<secret>" \
        --ipc=host \
        lmsysorg/sglang:latest \
        python3 -m sglang.launch_server \
            --model-path "aarishshahmohsin/got_ocr_2" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "aarishshahmohsin/got_ocr_2",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use aarishshahmohsin/got_ocr_2 with Docker Model Runner:

    docker model run hf.co/aarishshahmohsin/got_ocr_2
got_ocr_2
1.43 GB
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  • 1 contributor
History: 2 commits
aarishshahmohsin's picture
aarishshahmohsin
uploaded
7d26ea3 verified over 1 year ago
  • .gitattributes
    1.55 kB
    uploaded over 1 year ago
  • README.md
    4.09 kB
    uploaded over 1 year ago
  • config.json
    986 Bytes
    uploaded over 1 year ago
  • generation_config.json
    123 Bytes
    uploaded over 1 year ago
  • got_vision_b.py
    16.6 kB
    uploaded over 1 year ago
  • model.safetensors
    1.43 GB
    xet
    uploaded over 1 year ago
  • modeling_GOT.py
    33.8 kB
    uploaded over 1 year ago
  • qwen.tiktoken
    2.71 MB
    uploaded over 1 year ago
  • render_tools.py
    2.09 kB
    uploaded over 1 year ago
  • special_tokens_map.json
    158 Bytes
    uploaded over 1 year ago
  • tokenization_qwen.py
    9.73 kB
    uploaded over 1 year ago
  • tokenizer_config.json
    314 Bytes
    uploaded over 1 year ago