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Thibalte
/
captionning_project

Image-to-Text
Transformers
Safetensors
vision-encoder-decoder
image-text-to-text
image-captionning
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use Thibalte/captionning_project 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="Thibalte/captionning_project")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForImageTextToText
    
    tokenizer = AutoTokenizer.from_pretrained("Thibalte/captionning_project")
    model = AutoModelForImageTextToText.from_pretrained("Thibalte/captionning_project")
  • Notebooks
  • Google Colab
  • Kaggle
captionning_project
958 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
Thibalte's picture
Thibalte
Update README.md
5379b0e over 2 years ago
  • .gitattributes
    1.52 kB
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  • README.md
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  • config.json
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  • generation_config.json
    149 Bytes
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  • merges.txt
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  • model.safetensors
    957 MB
    xet
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  • preprocessor_config.json
    325 Bytes
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  • special_tokens_map.json
    470 Bytes
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  • tokenizer_config.json
    525 Bytes
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  • vocab.json
    999 kB
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