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HuggingFaceM4
/
tiny-random-idefics

Image-Text-to-Text
Transformers
PyTorch
idefics
text-generation-inference
Model card Files Files and versions
xet
Community
8

Instructions to use HuggingFaceM4/tiny-random-idefics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use HuggingFaceM4/tiny-random-idefics with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="HuggingFaceM4/tiny-random-idefics")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("HuggingFaceM4/tiny-random-idefics")
    model = AutoModelForImageTextToText.from_pretrained("HuggingFaceM4/tiny-random-idefics")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use HuggingFaceM4/tiny-random-idefics with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "HuggingFaceM4/tiny-random-idefics"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "HuggingFaceM4/tiny-random-idefics",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/HuggingFaceM4/tiny-random-idefics
  • SGLang

    How to use HuggingFaceM4/tiny-random-idefics 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 "HuggingFaceM4/tiny-random-idefics" \
        --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": "HuggingFaceM4/tiny-random-idefics",
    		"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 "HuggingFaceM4/tiny-random-idefics" \
            --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": "HuggingFaceM4/tiny-random-idefics",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use HuggingFaceM4/tiny-random-idefics with Docker Model Runner:

    docker model run hf.co/HuggingFaceM4/tiny-random-idefics
tiny-random-idefics
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  • 5 contributors
History: 15 commits
stas's picture
stas
set the correct vision_config.hidden_act
8b0de4d over 2 years ago
  • .gitattributes
    1.48 kB
    clone HuggingFaceM4/tiny-random-LlamaForCausalLM and rename almost 3 years ago
  • added_tokens.json
    61 Bytes
    tokenizer almost 3 years ago
  • config.json
    1.41 kB
    set the correct vision_config.hidden_act over 2 years ago
  • generation_config.json
    162 Bytes
    fix almost 3 years ago
  • preprocessor_config.json
    280 Bytes
    add image_num_channels almost 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    6.47 MB
    xet
    fix almost 3 years ago
  • special_tokens_map.json
    770 Bytes
    tokenizer almost 3 years ago
  • tokenizer.model
    500 kB
    xet
    tokenizer almost 3 years ago
  • tokenizer_config.json
    896 Bytes
    enable legacy=True almost 3 years ago