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minwook
/
git-base-cartoon

Image-Text-to-Text
Transformers
TensorBoard
Safetensors
git
Generated from Trainer
Model card Files Files and versions
xet
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Instructions to use minwook/git-base-cartoon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use minwook/git-base-cartoon with Transformers:

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

    How to use minwook/git-base-cartoon with vLLM:

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

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

    How to use minwook/git-base-cartoon with Docker Model Runner:

    docker model run hf.co/minwook/git-base-cartoon
git-base-cartoon / runs
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  • 1 contributor
History: 23 commits
minwook's picture
minwook
Model save
c9e50f0 verified almost 2 years ago
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  • Aug02_04-43-52_f1854a455c6e
    Training in progress, step 50 almost 2 years ago
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    Model save almost 2 years ago
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    Model save almost 2 years ago
  • Aug02_04-50-21_5f45d7a397b8
    Model save almost 2 years ago
  • Aug02_04-52-33_f1854a455c6e
    Training in progress, step 50 almost 2 years ago
  • Aug02_05-04-22_32beb6746cb5
    Model save almost 2 years ago
  • Aug02_05-05-34_f1854a455c6e
    Model save almost 2 years ago
  • Jul31_05-30-06_a10eae298346
    Training in progress, step 50 almost 2 years ago
  • Jul31_05-42-20_80282c379916
    Training in progress, step 280 almost 2 years ago