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Mayank1309
/
mayankBLIP

Image-Text-to-Text
Transformers
Safetensors
instructblip
Model card Files Files and versions
xet
Community

Instructions to use Mayank1309/mayankBLIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Mayank1309/mayankBLIP with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="Mayank1309/mayankBLIP")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("Mayank1309/mayankBLIP")
    model = AutoModelForImageTextToText.from_pretrained("Mayank1309/mayankBLIP")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use Mayank1309/mayankBLIP with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Mayank1309/mayankBLIP"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Mayank1309/mayankBLIP",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/Mayank1309/mayankBLIP
  • SGLang

    How to use Mayank1309/mayankBLIP 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 "Mayank1309/mayankBLIP" \
        --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": "Mayank1309/mayankBLIP",
    		"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 "Mayank1309/mayankBLIP" \
            --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": "Mayank1309/mayankBLIP",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use Mayank1309/mayankBLIP with Docker Model Runner:

    docker model run hf.co/Mayank1309/mayankBLIP
mayankBLIP
2.95 kB
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  • 1 contributor
History: 2 commits
Mayank1309's picture
Mayank1309
Training in progress
55fb8dc over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • config.json
    1.19 kB
    Training in progress over 2 years ago
  • generation_config.json
    138 Bytes
    Training in progress over 2 years ago
  • model.safetensors
    104 Bytes
    xet
    Training in progress over 2 years ago