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 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BiRefNet
How to use ZhengPeng7/BiRefNet with BiRefNet:
# Option 1: use with transformers from transformers import AutoModelForImageSegmentation birefnet = AutoModelForImageSegmentation.from_pretrained("ZhengPeng7/BiRefNet", 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") - Transformers
How to use ZhengPeng7/BiRefNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="ZhengPeng7/BiRefNet", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("ZhengPeng7/BiRefNet", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Request for license clarification
#23
by tokkiJK - opened
Hello,
We are considering ZhengPeng7/BiRefNet for use in a commercial service. The model would run only on our server, and users would receive only the output images.
The model card indicates MIT, and we found an MIT license in the linked GitHub repository. Could you please clarify whether the Hugging Face model weights are also covered by the MIT License?
If so, could you please share the required copyright notice and consider adding a LICENSE or NOTICE file to this repository that explicitly covers the model weights?
Thank you for your help.
You can find the license I set in the model card of each HF model.