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ZQL9711
/
RMBG-2-Matting

Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
Transformers.js
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Model card Files Files and versions
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Instructions to use ZQL9711/RMBG-2-Matting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ZQL9711/RMBG-2-Matting with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-segmentation", model="ZQL9711/RMBG-2-Matting", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForImageSegmentation
    model = AutoModelForImageSegmentation.from_pretrained("ZQL9711/RMBG-2-Matting", trust_remote_code=True, dtype="auto")
  • Transformers.js

    How to use ZQL9711/RMBG-2-Matting with Transformers.js:

    // npm i @huggingface/transformers
    import { pipeline } from '@huggingface/transformers';
    
    // Allocate pipeline
    const pipe = await pipeline('image-segmentation', 'ZQL9711/RMBG-2-Matting');
  • Notebooks
  • Google Colab
  • Kaggle
RMBG-2-Matting / onnx
3.59 GB
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  • 1 contributor
History: 1 commit
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ZQL9711
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