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Hellraiser24
/
git-base-textvqa

Image-Text-to-Text
Transformers
PyTorch
TensorBoard
git
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use Hellraiser24/git-base-textvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Hellraiser24/git-base-textvqa with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="Hellraiser24/git-base-textvqa")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("Hellraiser24/git-base-textvqa")
    model = AutoModelForImageTextToText.from_pretrained("Hellraiser24/git-base-textvqa")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use Hellraiser24/git-base-textvqa with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Hellraiser24/git-base-textvqa"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Hellraiser24/git-base-textvqa",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/Hellraiser24/git-base-textvqa
  • SGLang

    How to use Hellraiser24/git-base-textvqa 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 "Hellraiser24/git-base-textvqa" \
        --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": "Hellraiser24/git-base-textvqa",
    		"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 "Hellraiser24/git-base-textvqa" \
            --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": "Hellraiser24/git-base-textvqa",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use Hellraiser24/git-base-textvqa with Docker Model Runner:

    docker model run hf.co/Hellraiser24/git-base-textvqa
git-base-textvqa
709 MB
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  • 1 contributor
History: 6 commits
Hellraiser24's picture
Hellraiser24
update model card README.md
60b2078 almost 3 years ago
  • runs
    Model save almost 3 years ago
  • .gitattributes
    1.48 kB
    initial commit almost 3 years ago
  • .gitignore
    13 Bytes
    Training in progress, step 2000 almost 3 years ago
  • README.md
    2.03 kB
    update model card README.md almost 3 years ago
  • config.json
    2.9 kB
    Training in progress, step 2000 almost 3 years ago
  • generation_config.json
    136 Bytes
    Model save almost 3 years ago
  • pytorch_model.bin
    709 MB
    xet
    Model save almost 3 years ago
  • training_args.bin

    Detected Pickle imports (6)

    • "transformers.trainer_utils.SchedulerType",
    • "transformers.training_args.OptimizerNames",
    • "transformers.trainer_utils.HubStrategy",
    • "transformers.training_args.TrainingArguments",
    • "transformers.trainer_utils.IntervalStrategy",
    • "torch.device"

    How to fix it?

    3.58 kB
    xet
    Training in progress, step 2000 almost 3 years ago