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tuandao-zenai
/
rm_bg

Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
Transformers.js
remove background
background
background-removal
Pytorch
vision
legal liability
custom_code
Model card Files Files and versions
xet
Community

Instructions to use tuandao-zenai/rm_bg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use tuandao-zenai/rm_bg with Transformers:

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

    How to use tuandao-zenai/rm_bg with Transformers.js:

    // npm i @huggingface/transformers
    import { pipeline } from '@huggingface/transformers';
    
    // Allocate pipeline
    const pipe = await pipeline('image-segmentation', 'tuandao-zenai/rm_bg');
  • Notebooks
  • Google Colab
  • Kaggle
rm_bg / onnx
Ctrl+K
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  • 1 contributor
History: 1 commit
tuandao-zenai's picture
tuandao-zenai
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  • model.onnx
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  • model_bnb4.onnx
    355 MB
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  • model_fp16.onnx
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  • model_int8.onnx
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  • model_q4.onnx
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  • model_q4f16.onnx
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  • model_quantized.onnx
    366 MB
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  • model_uint8.onnx
    366 MB
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