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Mouwiya
/
BLIP_image_captioning

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

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

  • Libraries
  • Transformers

    How to use Mouwiya/BLIP_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="Mouwiya/BLIP_image_captioning")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("Mouwiya/BLIP_image_captioning")
    model = AutoModelForImageTextToText.from_pretrained("Mouwiya/BLIP_image_captioning")
  • Notebooks
  • Google Colab
  • Kaggle
BLIP_image_captioning
991 MB
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  • 1 contributor
History: 6 commits
Mouwiya's picture
Mouwiya
Update README.md
09e8a85 verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    2.65 kB
    Update README.md almost 2 years ago
  • config.json
    681 Bytes
    Upload BlipForConditionalGeneration almost 2 years ago
  • generation_config.json
    136 Bytes
    Upload BlipForConditionalGeneration almost 2 years ago
  • model.safetensors
    990 MB
    xet
    Upload BlipForConditionalGeneration almost 2 years ago
  • preprocessor_config.json
    706 Bytes
    Upload processor almost 2 years ago
  • special_tokens_map.json
    695 Bytes
    Upload processor almost 2 years ago
  • tokenizer.json
    711 kB
    Upload processor almost 2 years ago
  • tokenizer_config.json
    1.35 kB
    Upload processor almost 2 years ago
  • vocab.txt
    232 kB
    Upload processor almost 2 years ago