Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
Transformers.js
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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
- Xet hash:
- 2d2acc241f057922ac38e59005abc724eabb409d288236665a17a209c1aec199
- Size of remote file:
- 366 MB
- SHA256:
- fcea23951a378f92634834888896cc1eec54655366ae6e949282646ce17c5420
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