Xenova/deit-base-distilled-patch16-384
By Xenova · ↓ 14 · ♥ 0 · Updated 2025-06-27
What's in this repo
This page lists the files in Xenova/deit-base-distilled-patch16-384, including model.onnx, model_bnb4.onnx, model_fp16.onnx and more.
- 7 ONNX models (.onnx files)
- 12 files, including 7 .onnx, 3 .json, 1 .md
- Last updated 2025-06-27
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/model.onnx | — | Download |
| onnx/model_bnb4.onnx | — | Download |
| onnx/model_fp16.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
https://huggingface.co/facebook/deit-base-distilled-patch16-384 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
Example: Classify an image.
import { pipeline } from '@huggingface/transformers';
const classifier = await pipeline('image-classification', 'Xenova/deit-base-distilled-patch16-384');
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/tiger.jpg';
const output = await classifier(url);
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: 2023-08-26
Updated: 2025-06-27
View on Hugging Face