Instructions to use studioludens/birefnet-lite-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use studioludens/birefnet-lite-512 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-segmentation', 'studioludens/birefnet-lite-512'); - BiRefNet
How to use studioludens/birefnet-lite-512 with BiRefNet:
# Option 1: use with transformers from transformers import AutoModelForImageSegmentation birefnet = AutoModelForImageSegmentation.from_pretrained("studioludens/birefnet-lite-512", 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("studioludens/birefnet-lite-512") - Notebooks
- Google Colab
- Kaggle
Request for license clarification
Hello,
We are considering studioludens/birefnet-lite-512 for use in a commercial web service. The ONNX model files would be downloaded and run in users’ browsers.
Could you please clarify whether the ONNX model weights in this repository are covered by the MIT License and may be redistributed for commercial browser-based use?
As the model card describes this repository as an ONNX re-export of ZhengPeng7/BiRefNet_lite, could you also clarify whether the original model weights permit this conversion and redistribution under MIT?
If possible, please share the required copyright notice and consider adding a LICENSE or NOTICE file that explicitly covers the model files.
Thank you for your help.