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tuman
/
vit-rugpt2-image-captioning

Image-to-Text
Transformers
PyTorch
Russian
vision-encoder-decoder
image-text-to-text
image-captioning
Model card Files Files and versions
xet
Community
1

Instructions to use tuman/vit-rugpt2-image-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use tuman/vit-rugpt2-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="tuman/vit-rugpt2-image-captioning")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForImageTextToText
    
    tokenizer = AutoTokenizer.from_pretrained("tuman/vit-rugpt2-image-captioning")
    model = AutoModelForImageTextToText.from_pretrained("tuman/vit-rugpt2-image-captioning")
  • Notebooks
  • Google Colab
  • Kaggle
vit-rugpt2-image-captioning
4.5 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
tuman's picture
tuman
Update README.md
a5cf023 over 3 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • README.md
    2.26 kB
    Update README.md over 3 years ago
  • config.json
    4.93 kB
    Initial commit over 3 years ago
  • merges.txt
    1.27 MB
    Initial commit over 3 years ago
  • preprocessor_config.json
    228 Bytes
    Initial commit over 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    4.5 GB
    xet
    Initial commit over 3 years ago
  • special_tokens_map.json
    217 Bytes
    Initial commit over 3 years ago
  • tokenizer_config.json
    780 Bytes
    Initial commit over 3 years ago
  • vocab.json
    1.81 MB
    Initial commit over 3 years ago