Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
Transformers.js
remove background
background
background-removal
Pytorch
vision
legal liability
custom_code
Instructions to use mohantesting/remove_background with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohantesting/remove_background with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="mohantesting/remove_background", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("mohantesting/remove_background", trust_remote_code=True, dtype="auto") - Transformers.js
How to use mohantesting/remove_background with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-segmentation', 'mohantesting/remove_background'); - Notebooks
- Google Colab
- Kaggle
File size: 405 Bytes
ddd449c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"_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
} |