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eagle0504
/
blip-vqa-finetuned-draft-1

Question Answering
Transformers
Safetensors
blip
image-text-to-text
vision-language
image-to-text
fine-tuned
vqa
Model card Files Files and versions
xet
Community

Instructions to use eagle0504/blip-vqa-finetuned-draft-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use eagle0504/blip-vqa-finetuned-draft-1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("question-answering", model="eagle0504/blip-vqa-finetuned-draft-1")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("eagle0504/blip-vqa-finetuned-draft-1")
    model = AutoModelForImageTextToText.from_pretrained("eagle0504/blip-vqa-finetuned-draft-1")
  • Notebooks
  • Google Colab
  • Kaggle
blip-vqa-finetuned-draft-1
991 MB
Ctrl+K
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  • 1 contributor
History: 4 commits
eagle0504's picture
eagle0504
Update README.md
fd4a5c4 verified 10 months ago
  • .gitattributes
    1.52 kB
    initial commit 10 months ago
  • README.md
    5.15 kB
    Update README.md 10 months ago
  • config.json
    1.37 kB
    Upload BlipForConditionalGeneration 10 months ago
  • generation_config.json
    141 Bytes
    Upload BlipForConditionalGeneration 10 months ago
  • model.safetensors
    990 MB
    xet
    Upload BlipForConditionalGeneration 10 months ago
  • preprocessor_config.json
    431 Bytes
    Upload processor 10 months ago
  • special_tokens_map.json
    695 Bytes
    Upload processor 10 months ago
  • tokenizer.json
    712 kB
    Upload processor 10 months ago
  • tokenizer_config.json
    1.38 kB
    Upload processor 10 months ago
  • vocab.txt
    232 kB
    Upload processor 10 months ago