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dineshcr7
/
Type_MediVQA

Visual Question Answering
Transformers
Safetensors
blip
Model card Files Files and versions
xet
Community

Instructions to use dineshcr7/Type_MediVQA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use dineshcr7/Type_MediVQA with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("visual-question-answering", model="dineshcr7/Type_MediVQA")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering
    
    processor = AutoProcessor.from_pretrained("dineshcr7/Type_MediVQA")
    model = AutoModelForVisualQuestionAnswering.from_pretrained("dineshcr7/Type_MediVQA")
  • Notebooks
  • Google Colab
  • Kaggle
Type_MediVQA
1.54 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 10 commits
dineshcr7's picture
dineshcr7
Upload processor
70c739d over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • config.json
    638 Bytes
    Upload BlipForQuestionAnswering over 2 years ago
  • generation_config.json
    136 Bytes
    Upload BlipForQuestionAnswering over 2 years ago
  • model.safetensors
    1.54 GB
    xet
    Upload BlipForQuestionAnswering over 2 years ago
  • preprocessor_config.json
    471 Bytes
    Upload processor over 2 years ago
  • special_tokens_map.json
    125 Bytes
    Upload tokenizer over 2 years ago
  • tokenizer.json
    712 kB
    Upload tokenizer over 2 years ago
  • tokenizer_config.json
    1.38 kB
    Upload tokenizer over 2 years ago
  • vocab.txt
    232 kB
    Upload tokenizer over 2 years ago