Instructions to use facebook/dinov2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/dinov2-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="facebook/dinov2-base")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("facebook/dinov2-base") model = AutoModel.from_pretrained("facebook/dinov2-base") - Notebooks
- Google Colab
- Kaggle
FlaxDinov2-base
#12
by MHRDYN7 - opened
- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:19e34b5ded1143464704df7455a4de8ba934605545584e8e08420513695dc58f
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size 346329750
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