vinip122/nllb-200-distilled-600M
By vinip122 · ↓ 11 · ♥ 0 · Updated 2026-03-03
What's in this repo
This page lists the files in vinip122/nllb-200-distilled-600M, including decoder_model.onnx, decoder_model_bnb4.onnx, decoder_model_fp16.onnx and more.
- 32 ONNX models (.onnx files)
- 41 files, including 32 .onnx, 6 .json, 1 .md, 1 .model
- Last updated 2026-03-03
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/decoder_model.onnx | — | Download |
| onnx/decoder_model_bnb4.onnx | — | Download |
| onnx/decoder_model_fp16.onnx | — | Download |
| onnx/decoder_model_int8.onnx | — | Download |
| onnx/decoder_model_merged.onnx | — | Download |
| onnx/decoder_model_merged_bnb4.onnx | — | Download |
| onnx/decoder_model_merged_fp16.onnx | — | Download |
| onnx/decoder_model_merged_int8.onnx | — | Download |
| onnx/decoder_model_merged_q4.onnx | — | Download |
| onnx/decoder_model_merged_q4f16.onnx | — | Download |
Showing 10 of 32 .onnx files — see the full file list on the right.
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
https://huggingface.co/facebook/nllb-200-distilled-600M with ONNX weights to be compatible with Transformers.js.
Usage (Transformers.js)
If you haven't already, you can install the Transformers.js JavaScript library from NPM using:
npm i @huggingface/transformers
You can then perform multilingual translation like this:
import { pipeline } from '@huggingface/transformers';
// Create a translation pipeline
const translator = await pipeline('translation', 'Xenova/nllb-200-distilled-600M');
// Translate text from Hindi to French
const output = await translator('जीवन एक चॉकलेट बॉक्स की तरह है।', {
src_lang: 'hin_Deva', // Hindi
tgt_lang: 'fra_Latn', // French
});
console.log(output);
// [{ translation_text: 'La vie est comme une boîte à chocolat.' }]
See here for the full list of languages and their corresponding codes.
Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).
Model info
Created: 2026-03-03
Updated: 2026-03-03
View on Hugging FaceFiles (41)
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