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nnpy
/
blip-image-captioning

Image-to-Text
Transformers
PyTorch
Safetensors
blip
image-text-to-text
Model card Files Files and versions
xet
Community
4

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

  • Libraries
  • Transformers

    How to use nnpy/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="nnpy/blip-image-captioning")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("nnpy/blip-image-captioning")
    model = AutoModelForImageTextToText.from_pretrained("nnpy/blip-image-captioning")
  • Notebooks
  • Google Colab
  • Kaggle
blip-image-captioning
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  • 3 contributors
History: 11 commits
prasanna2003's picture
prasanna2003
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model (#4)
b413986 almost 3 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • README.md
    737 Bytes
    Update README.md almost 3 years ago
  • config.json
    4.71 kB
    Upload BlipForConditionalGeneration (#1) almost 3 years ago
  • model.safetensors
    990 MB
    xet
    Adding `safetensors` variant of this model (#4) almost 3 years ago
  • preprocessor_config.json
    287 Bytes
    Upload 5 files almost 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

    • "torch.FloatStorage",
    • "torch.LongStorage",
    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict"

    What is a pickle import?

    990 MB
    xet
    Upload BlipForConditionalGeneration (#1) almost 3 years ago
  • special_tokens_map.json
    125 Bytes
    Upload 5 files almost 3 years ago
  • tokenizer.json
    711 kB
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  • tokenizer_config.json
    506 Bytes
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  • vocab.txt
    232 kB
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