Image Segmentation
BiRefNet
Safetensors
Transformers
background-removal
mask-generation
Dichotomous Image Segmentation
Camouflaged Object Detection
Salient Object Detection
pytorch_model_hub_mixin
model_hub_mixin
custom_code
Instructions to use ZhengPeng7/BiRefNet_dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BiRefNet
How to use ZhengPeng7/BiRefNet_dynamic with BiRefNet:
# Option 1: use with transformers from transformers import AutoModelForImageSegmentation birefnet = AutoModelForImageSegmentation.from_pretrained("ZhengPeng7/BiRefNet_dynamic", trust_remote_code=True)# Option 2: use with BiRefNet # Install from https://github.com/ZhengPeng7/BiRefNet from models.birefnet import BiRefNet model = BiRefNet.from_pretrained("ZhengPeng7/BiRefNet_dynamic") - Transformers
How to use ZhengPeng7/BiRefNet_dynamic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="ZhengPeng7/BiRefNet_dynamic", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("ZhengPeng7/BiRefNet_dynamic", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Remove Transformers.js tag
#1
by Xenova HF Staff - opened
Not directly compatible with Transformers.js since the repo is missing ONNX weights
Xenova changed pull request title from Not directly compatible with Transformers.js since the repo is missing ONNX weights to Remove Transformers.js tag
ZhengPeng7 changed pull request status to merged