Update model-card for DINOv2 #37104
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Update model-card for DINOv2 #37104
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stevhliu
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Mar 31, 2025
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
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@stevhliu All requested changes have been made in the latest commit 👍🏻 |
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@stevhliu I have added a quantization example as requested 👍🏻 |
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[docs] Update model-card for DINOv2
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| ## Resources | ||
| url = 'http://images.cocodataset.org/val2017/000000039769.jpg' | ||
| image = Image.open(requests.get(url, stream=True).raw) | ||
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| A list of official Hugging Face and community (indicated by 🌎) resources to help you get started with DINOv2. | ||
| processor = AutoImageProcessor.from_pretrained('facebook/dinov2-base') | ||
| model = AutoModel.from_pretrained('facebook/dinov2-base') | ||
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| - Demo notebooks for DINOv2 can be found [here](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/DINOv2). 🌎 | ||
| inputs = processor(images=image, return_tensors="pt") | ||
| outputs = model(**inputs) | ||
| last_hidden_states = outputs[0] | ||
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| <PipelineTag pipeline="image-classification"/> | ||
| # We have to force return_dict=False for tracing | ||
| model.config.return_dict = False | ||
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| - [`Dinov2ForImageClassification`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/image-classification) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb). | ||
| - See also: [Image classification task guide](../tasks/image_classification) | ||
| with torch.no_grad(): | ||
| traced_model = torch.jit.trace(model, [inputs.pixel_values]) | ||
| traced_outputs = traced_model(inputs.pixel_values) | ||
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| If you're interested in submitting a resource to be included here, please feel free to open a Pull Request and we'll review it! The resource should ideally demonstrate something new instead of duplicating an existing resource. |
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Providing code snippets is great, however it would be super nice to keep resources within docs, they usually provide more in-depth view of the model, e.g. finetuning 🤗
cc @stevhliu
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What does this PR do?
This PR updates the model-card for the
dinov2model, as described in #36979, in an attempt to standardize all model-cards.Before submitting
Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.
@stevhliu