Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
Transformers.js
remove background
background
background-removal
Pytorch
vision
legal liability
custom_code
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
- Xet hash:
- 8996d11c042b8cb8b7f508245ea29f6376b6ad49d9ead0658af2083802b1b7e1
- Size of remote file:
- 514 MB
- SHA256:
- 9dc47db40d113090ba5d7a13d8fcfd9ee4eda510ce92613219b2fe19da4746f6
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