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theIndividual
/
Florence-2-base

Image-to-Text
Transformers
PyTorch
florence2
image-text-to-text
vision
custom_code
Model card Files Files and versions
xet
Community

Instructions to use theIndividual/Florence-2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use theIndividual/Florence-2-base 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="theIndividual/Florence-2-base", trust_remote_code=True)
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("theIndividual/Florence-2-base", trust_remote_code=True)
    model = AutoModelForImageTextToText.from_pretrained("theIndividual/Florence-2-base", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
Florence-2-base
467 MB
Ctrl+K
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  • 3 contributors
History: 10 commits
Pedro Cavalcanti
changed: file
11931df almost 2 years ago
  • .gitattributes
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  • CODE_OF_CONDUCT.md
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  • LICENSE
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  • README.md
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  • SECURITY.md
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  • SUPPORT.md
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  • config.json
    2.43 kB
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  • configuration_florence2.py
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  • modeling_florence2.py
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  • preprocessor_config.json
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  • processing_florence2.py
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  • pytorch_model.bin

    Detected Pickle imports (3)

    • "torch.HalfStorage",
    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    464 MB
    xet
    init_model (#1) almost 2 years ago
  • tokenizer.json
    1.36 MB
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  • tokenizer_config.json
    34 Bytes
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  • vocab.json
    1.1 MB
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