---
license: mit
library_name: transformers.js
base_model: ZhengPeng7/BiRefNet_lite
pipeline_tag: image-segmentation
tags:
  - onnx
  - birefnet
  - background-removal
  - dichotomous-image-segmentation
  - webgpu
  - transformers.js
  - onnxruntime-web
---

# BiRefNet-lite 1024 (ONNX, WebGPU-runnable)

BiRefNet-lite at 1024 × 1024 as an fp16 ONNX export whose graph is patched to run on WebGPU in the browser; the weights are unchanged. [Card Anvil](https://github.com/Card-Anvil) uses it with [Transformers.js](https://github.com/huggingface/transformers.js) to select the main subject of card art.

These are unchanged copies of the files in [`jiabins0303/birefnet-lite-1024-webgpu`](https://huggingface.co/jiabins0303/birefnet-lite-1024-webgpu) at commit [`1ad01ce`](https://huggingface.co/jiabins0303/birefnet-lite-1024-webgpu/tree/1ad01cef0f4101a285c5a3e0bd7f15597d93403f), at the same paths, kept here so the app loads files that can't change under it.

| Files | What they are | Loaded by Card Anvil |
| --- | --- | --- |
| `config.json`, `preprocessor_config.json`, `onnx/model_fp16.onnx` | The model | Yes |
| `scripts/patch_split.py`, `scripts/patch_deform.py`, `scripts/verify_patch.py` | The scripts that rewrote the graph to run on WebGPU, and the check that the result matches the original | No, kept for later |
| `SOURCE_README.md` | The source repo's README: how and why the graph was patched, and how it was verified | No |

## Credits and licence

- Model: [BiRefNet](https://github.com/ZhengPeng7/BiRefNet) by Peng Zheng et al. ([`ZhengPeng7/BiRefNet_lite`](https://huggingface.co/ZhengPeng7/BiRefNet_lite)), from *Bilateral Reference for High-Resolution Dichotomous Image Segmentation* (CAAI AIR 2024).
- WebGPU-runnable export: [`jiabins0303/birefnet-lite-1024-webgpu`](https://huggingface.co/jiabins0303/birefnet-lite-1024-webgpu).

Licensed under the MIT License, as the original model is. See [`LICENSE`](LICENSE).