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cocktailpeanut
/
rm

Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
Transformers.js
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Instructions to use cocktailpeanut/rm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use cocktailpeanut/rm with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-segmentation", model="cocktailpeanut/rm", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForImageSegmentation
    model = AutoModelForImageSegmentation.from_pretrained("cocktailpeanut/rm", trust_remote_code=True, dtype="auto")
  • Transformers.js

    How to use cocktailpeanut/rm with Transformers.js:

    // npm i @huggingface/transformers
    import { pipeline } from '@huggingface/transformers';
    
    // Allocate pipeline
    const pipe = await pipeline('image-segmentation', 'cocktailpeanut/rm');
  • Notebooks
  • Google Colab
  • Kaggle
rm
5.37 GB
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  • 1 contributor
History: 2 commits
cocktailpeanut's picture
cocktailpeanut
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  • .gitattributes
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  • BiRefNet_config.py
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  • README.md
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  • birefnet.py
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  • config.json
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  • model.safetensors
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  • preprocessor_config.json
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  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

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  • t4.png
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