Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
Transformers.js
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Instructions to use aoiandroid/RMBG-2-Matting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aoiandroid/RMBG-2-Matting with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="aoiandroid/RMBG-2-Matting", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("aoiandroid/RMBG-2-Matting", trust_remote_code=True, dtype="auto") - Transformers.js
How to use aoiandroid/RMBG-2-Matting with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-segmentation', 'aoiandroid/RMBG-2-Matting'); - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "ZhengPeng7/BiRefNet", | |
| "architectures": [ | |
| "BiRefNet" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "BiRefNet_config.BiRefNetConfig", | |
| "AutoModelForImageSegmentation": "birefnet.BiRefNet" | |
| }, | |
| "custom_pipelines": { | |
| "image-segmentation": { | |
| "pt": [ | |
| "AutoModelForImageSegmentation" | |
| ], | |
| "tf": [], | |
| "type": "image" | |
| } | |
| }, | |
| "bb_pretrained": false | |
| } |