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prithivMLmods
/
Florence-2-VLM-Doc-VQA

Image-to-Text
Transformers
Safetensors
English
florence2
image-text-to-text
finetune
VQA
VLM
custom_code
Model card Files Files and versions
xet

Instructions to use prithivMLmods/Florence-2-VLM-Doc-VQA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use prithivMLmods/Florence-2-VLM-Doc-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="prithivMLmods/Florence-2-VLM-Doc-VQA", trust_remote_code=True)
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("prithivMLmods/Florence-2-VLM-Doc-VQA", trust_remote_code=True)
    model = AutoModelForImageTextToText.from_pretrained("prithivMLmods/Florence-2-VLM-Doc-VQA", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
Florence-2-VLM-Doc-VQA
1.09 GB
Ctrl+K
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  • 1 contributor
History: 7 commits
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prithivMLmods
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  • added_tokens.json
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  • config.json
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  • generation_config.json
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  • merges.txt
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  • model.safetensors
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  • preprocessor_config.json
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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  • vocab.json
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