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babylm
/
git-2024

Image-Text-to-Text
Transformers
PyTorch
git
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use babylm/git-2024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use babylm/git-2024 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="babylm/git-2024", trust_remote_code=True)
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("babylm/git-2024", trust_remote_code=True)
    model = AutoModelForImageTextToText.from_pretrained("babylm/git-2024", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use babylm/git-2024 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "babylm/git-2024"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "babylm/git-2024",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/babylm/git-2024
  • SGLang

    How to use babylm/git-2024 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 "babylm/git-2024" \
        --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": "babylm/git-2024",
    		"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 "babylm/git-2024" \
            --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": "babylm/git-2024",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use babylm/git-2024 with Docker Model Runner:

    docker model run hf.co/babylm/git-2024
git-2024
1.59 GB
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  • 2 contributors
History: 8 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
f6b41b2 verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • LICENSE
    1.08 kB
    add LICENSE almost 2 years ago
  • README.md
    21 Bytes
    initial commit about 2 years ago
  • config.json
    3.05 kB
    add support for sequence classification almost 2 years ago
  • configuration_git.py
    7.46 kB
    model upload about 2 years ago
  • generation_config.json
    136 Bytes
    model upload about 2 years ago
  • model.safetensors
    792 MB
    xet
    Adding `safetensors` variant of this model about 1 year ago
  • modeling_git.py
    9.66 kB
    minor fix for config class almost 2 years ago
  • preprocessor_config.json
    390 Bytes
    add processor json about 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    792 MB
    xet
    model for new text data and tokenizer almost 2 years ago
  • special_tokens_map.json
    95 Bytes
    model upload about 2 years ago
  • tokenizer.json
    2.14 MB
    model for new text data and tokenizer almost 2 years ago
  • tokenizer_config.json
    146 Bytes
    model upload about 2 years ago