onnx-community/MVANet-ONNX
By onnx-community · ↓ 8 · ♥ 0 · Updated 2025-08-18
What's in this repo
This page lists the files in onnx-community/MVANet-ONNX, including model.onnx, model_bnb4.onnx, model_fp16.onnx and more.
- 8 ONNX models (.onnx files)
- 12 files, including 8 .onnx, 2 .json, 1 .md
- Last updated 2025-08-18
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/model.onnx | — | Download |
| onnx/model_bnb4.onnx | — | Download |
| onnx/model_fp16.onnx | — | Download |
| onnx/model_int8.onnx | — | Download |
| onnx/model_q4.onnx | — | Download |
| onnx/model_q4f16.onnx | — | Download |
| onnx/model_quantized.onnx | — | Download |
| onnx/model_uint8.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
Usage (Transformers.js)
If you haven't already, you can install the Transformers.js JavaScript library from NPM using:
npm i @huggingface/transformers
Example: Remove background of an image
import { pipeline } from '@huggingface/transformers';
const segmenter = await pipeline('background-removal', 'onnx-community/MVANet-ONNX');
const url = 'https://images.pexels.com/photos/5965592/pexels-photo-5965592.jpeg?auto=compress&cs=tinysrgb&w=1024';
const output = await segmenter(url);
output[0].save('mask.png');
// You can also use `output[0].toCanvas()` or `await output[0].toBlob()` if you would like to access the output without saving.
Model info
image-segmentation
transformers.js
transformers.js
onnx
swin
background-removal
image-segmentation
license:mit
region:us
↓ 8
♥ 0
Created: 2025-03-03
Updated: 2025-08-18
View on Hugging FaceFiles (12)
.gitattributes
README.md
config.json
onnx/model.onnx
ONNX
onnx/model_bnb4.onnx
ONNX
onnx/model_fp16.onnx
ONNX
onnx/model_int8.onnx
ONNX
onnx/model_q4.onnx
ONNX
onnx/model_q4f16.onnx
ONNX
onnx/model_quantized.onnx
ONNX
onnx/model_uint8.onnx
ONNX
preprocessor_config.json