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vkao8264
/
blip-yoda-captioning

Image-to-Text
Transformers
Safetensors
English
blip
image-text-to-text
Model card Files Files and versions
xet
Community

Instructions to use vkao8264/blip-yoda-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use vkao8264/blip-yoda-captioning 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="vkao8264/blip-yoda-captioning")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("vkao8264/blip-yoda-captioning")
    model = AutoModelForImageTextToText.from_pretrained("vkao8264/blip-yoda-captioning")
  • Notebooks
  • Google Colab
  • Kaggle
blip-yoda-captioning
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  • 1 contributor
History: 12 commits
vkao8264's picture
vkao8264
Update README.md
295823a verified 10 months ago
  • .gitattributes
    1.52 kB
    initial commit 11 months ago
  • README.md
    1.92 kB
    Update README.md 10 months ago
  • config.json
    684 Bytes
    Upload BlipForConditionalGeneration 11 months ago
  • generation_config.json
    143 Bytes
    Upload BlipForConditionalGeneration 11 months ago
  • handler.py
    2.27 kB
    Update handler.py 10 months ago
  • model.safetensors
    990 MB
    xet
    Upload BlipForConditionalGeneration 11 months ago