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alexbeta80
/
pix2struct_polizze

Image-Text-to-Text
Transformers
PyTorch
pix2struct
Model card Files Files and versions
xet
Community

Instructions to use alexbeta80/pix2struct_polizze with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use alexbeta80/pix2struct_polizze with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="alexbeta80/pix2struct_polizze")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("alexbeta80/pix2struct_polizze")
    model = AutoModelForImageTextToText.from_pretrained("alexbeta80/pix2struct_polizze")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use alexbeta80/pix2struct_polizze with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "alexbeta80/pix2struct_polizze"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "alexbeta80/pix2struct_polizze",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/alexbeta80/pix2struct_polizze
  • SGLang

    How to use alexbeta80/pix2struct_polizze 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 "alexbeta80/pix2struct_polizze" \
        --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": "alexbeta80/pix2struct_polizze",
    		"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 "alexbeta80/pix2struct_polizze" \
            --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": "alexbeta80/pix2struct_polizze",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use alexbeta80/pix2struct_polizze with Docker Model Runner:

    docker model run hf.co/alexbeta80/pix2struct_polizze
pix2struct_polizze
1.13 GB
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  • 1 contributor
History: 2 commits
alexbeta80's picture
alexbeta80
Upload Pix2StructForConditionalGeneration
23e5d48 about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • config.json
    890 Bytes
    Upload Pix2StructForConditionalGeneration about 2 years ago
  • generation_config.json
    164 Bytes
    Upload Pix2StructForConditionalGeneration about 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    1.13 GB
    xet
    Upload Pix2StructForConditionalGeneration about 2 years ago