Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

jaimin
/
Imagecap1

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

Instructions to use jaimin/Imagecap1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use jaimin/Imagecap1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="jaimin/Imagecap1")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("jaimin/Imagecap1")
    model = AutoModelForImageTextToText.from_pretrained("jaimin/Imagecap1")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use jaimin/Imagecap1 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "jaimin/Imagecap1"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "jaimin/Imagecap1",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/jaimin/Imagecap1
  • SGLang

    How to use jaimin/Imagecap1 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 "jaimin/Imagecap1" \
        --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": "jaimin/Imagecap1",
    		"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 "jaimin/Imagecap1" \
            --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": "jaimin/Imagecap1",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use jaimin/Imagecap1 with Docker Model Runner:

    docker model run hf.co/jaimin/Imagecap1
Imagecap1
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
jaimin's picture
jaimin
Upload 8 files
520f049 about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • config.json
    2.82 kB
    Upload 8 files about 3 years ago
  • generation_config.json
    141 Bytes
    Upload 8 files about 3 years ago
  • preprocessor_config.json
    503 Bytes
    Upload 8 files about 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    1.58 GB
    xet
    Upload 8 files about 3 years ago
  • special_tokens_map.json
    125 Bytes
    Upload 8 files about 3 years ago
  • tokenizer.json
    711 kB
    Upload 8 files about 3 years ago
  • tokenizer_config.json
    453 Bytes
    Upload 8 files about 3 years ago
  • vocab.txt
    232 kB
    Upload 8 files about 3 years ago