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Dinov2 Large

with ONNX weights to be compatible with Transformers.js.

KindOtherBase modelfacebook/dinov2-largeVersionRevision 8e0c7fb

Model source

Kind
Other
File size
165 MB–1.13 GB
Base model
facebook/dinov2-large
Version
vRevision 8e0c7fb
Updated
Sep 21, 2026
Downloads
301
Source
Hugging Face

Source description

https://huggingface.co/facebook/dinov2-large 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: Perform image feature extraction.

import { pipeline } from '@huggingface/transformers';

const image_feature_extractor = await pipeline('image-feature-extraction', 'Xenova/dinov2-large');
const url = 'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/cats.png';
const features = await image_feature_extractor(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).

Sources

1 source
Hugging FacePrimaryVersion 8e0c7fb0fac7eb045a12ae4b03d1d4b51becfd25
huggingface.co/Xenova/dinov2-large/tree/8e0c7fb0fac7eb045a12ae4b03d1d4b51becfd25

Verified Sep 9

Model artifacts

7 artifacts

onnx/model_bnb4.onnx

onnx · 167 MB · SHA-256 89d986d549ad…fd3c · Hugging Face

Download

onnx/model_fp16.onnx

onnx · 581 MB · SHA-256 f7971764ec1b…b70e · Hugging Face

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onnx/model_q4.onnx

onnx · 185 MB · SHA-256 f4dd5159a618…233d · Hugging Face

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onnx/model_q4f16.onnx

onnx · 165 MB · SHA-256 f3a1459463aa…2e4b · Hugging Face

Download

onnx/model_quantized.onnx

onnx · 297 MB · SHA-256 0d452c4f4b70…8750 · Hugging Face

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onnx/model_uint8.onnx

onnx · 291 MB · SHA-256 2bf201c18024…d07c · Hugging Face

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onnx/model.onnx

onnx · 1.13 GB · SHA-256 60743ada3c34…ff90 · Hugging Face

Download

Source excerpts

2 excerpts

--- base_model: facebook/dinov2-large library_name: transformers.js --- https://huggingface.co/facebook/dinov2-large with ONNX weights to be compatible with Transformers.js. ## Usage (Transformers.js) If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/transformers) using: ```bash npm i @huggingface/transformers ``` **Example:** Perform image feature extraction. ```js import { pipeline } from '@huggingface/transformers'; const image_feature_extractor = await pipeline('image-feature-extraction', 'Xenova/dinov2-large'); const url = 'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/cats.png'; const features = await image_feature_extractor(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](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).

Source context: 301 downloads · 1 likes · Pipeline image-feature-extraction · Library transformers.js · Repo Xenova/dinov2-large