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tifa-benchmark
/
promptcap-coco-vqa

Image-to-Text
Transformers
PyTorch
English
ofa
visual-question-answering
image-captioning
Model card Files Files and versions
xet
Community
2

Instructions to use tifa-benchmark/promptcap-coco-vqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use tifa-benchmark/promptcap-coco-vqa 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="tifa-benchmark/promptcap-coco-vqa")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("tifa-benchmark/promptcap-coco-vqa", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
promptcap-coco-vqa
2.45 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
yushihu's picture
yushihu
initial commit
9b1371d over 3 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago
  • README.md
    26 Bytes
    initial commit over 3 years ago
  • config.json
    1.4 kB
    initial commit over 3 years ago
  • merges.txt
    456 kB
    initial commit over 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    2.45 GB
    xet
    initial commit over 3 years ago
  • vocab.json
    899 kB
    initial commit over 3 years ago