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patricklabatut merged 2 commits into from
Sep 24, 2025
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Update README #212

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Update README with transformers and timm released versions supporting…
patricklabatut Sep 24, 2025
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Fix newlines
patricklabatut Sep 24, 2025
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🆕 [2025-08-14] :fire: DINOv3 backbones are now available in [Hugging Face Hub](https://huggingface.co/collections/facebook/dinov3-68924841bd6b561778e31009) and [supported](https://huggingface.co/docs/transformers/model_doc/dinov3) by the Hugging Face [Transformers](https://huggingface.co/docs/transformers/index) library
🆕 [2025-09-17] :fire: DINOv3 backbones are now supported by the [PyTorch Image Models / timm](https://github.com/huggingface/pytorch-image-models/) library starting with version [1.0.20](https://github.com/huggingface/pytorch-image-models/releases/tag/v1.0.20)

[2025-08-29] DINOv3 backbones are [supported](https://huggingface.co/docs/transformers/model_doc/dinov3) by released versions of the Hugging Face [Transformers](https://huggingface.co/docs/transformers/index) library starting with version [4.56.0](https://github.com/huggingface/transformers/releases/tag/v4.56.0)

[2025-08-14] DINOv3 backbones are now available in [Hugging Face Hub](https://huggingface.co/collections/facebook/dinov3-68924841bd6b561778e31009) and [supported](https://huggingface.co/docs/transformers/model_doc/dinov3) by the [development](https://github.com/huggingface/transformers/) version of the Hugging Face [Transformers](https://huggingface.co/docs/transformers/index) library

# DINOv3 🦖🦖🦖

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### Pretrained backbones (via Hugging Face [Transformers](https://huggingface.co/docs/transformers/))

All the backbones are available in the the [DINOv3](https://huggingface.co/collections/facebook/dinov3-68924841bd6b561778e31009) collection on Hugging Face Hub and supported via the Hugging Face [Transformers](https://huggingface.co/docs/transformers/index) library. Please refer to the corresponding documentation for usage, but below is a short example that demonstrates how to obtain an image embedding with either [Pipeline] or the [AutoModel] class.
All the backbones are available in the [DINOv3](https://huggingface.co/collections/facebook/dinov3-68924841bd6b561778e31009) collection on Hugging Face Hub and supported via the Hugging Face [Transformers](https://huggingface.co/docs/transformers/index) library (with released packages from version 4.56.0). Please refer to the corresponding documentation for usage, but below is a short example that demonstrates how to obtain an image embedding with either [Pipeline] or the [AutoModel] class.

```python
from transformers import pipeline
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