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cnmoro
/
mini-image-captioning

Image-to-Text
Transformers
Safetensors
English
vision-encoder-decoder
image-text-to-text
vit
bert
vision
caption
captioning
image
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use cnmoro/mini-image-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="cnmoro/mini-image-captioning")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForImageTextToText
    
    tokenizer = AutoTokenizer.from_pretrained("cnmoro/mini-image-captioning")
    model = AutoModelForImageTextToText.from_pretrained("cnmoro/mini-image-captioning")
  • Notebooks
  • Google Colab
  • Kaggle
mini-image-captioning
138 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
cnmoro's picture
cnmoro
Update README.md
292fe1c verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • New_york_times_square-terabass.jpg
    182 kB
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  • README.md
    1.63 kB
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  • config.json
    4.4 kB
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  • generation_config.json
    117 Bytes
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  • model.safetensors
    137 MB
    xet
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  • preprocessor_config.json
    325 Bytes
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    1.27 kB
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  • vocab.txt
    232 kB
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