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movementso
/
blip-image-captioning-large

Image-to-Text
Transformers
PyTorch
google-tensorflow TensorFlow
Safetensors
blip
image-text-to-text
image-captioning
Model card Files Files and versions
xet
Community
1

Instructions to use movementso/blip-image-captioning-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use movementso/blip-image-captioning-large with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5.
    # You must load the model directly (see below) or downgrade to v4.x with:
    # 'pip install "transformers<5.0.0'
    from transformers import pipeline
    
    pipe = pipeline("image-to-text", model="movementso/blip-image-captioning-large")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("movementso/blip-image-captioning-large")
    model = AutoModelForMultimodalLM.from_pretrained("movementso/blip-image-captioning-large", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
blip-image-captioning-large / __pycache__
1.55 kB
Ctrl+K
Ctrl+K
  • 6 contributors
History: 1 commit
smlparry
Add test
b730691 about 3 years ago
  • handler.cpython-310.pyc
    1.55 kB
    Add test about 3 years ago