Instructions to use hf-internal-testing/tiny-random-Dinov2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Dinov2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-Dinov2Model")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-Dinov2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Dinov2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 715b192ed7a6f0fdb8135ac6a3007ba7dc31d522d67c12293da2b477fc27c61d
- Size of remote file:
- 301 kB
- SHA256:
- 24dfb8724d2e57e282b00ce39fe94d276551f2243e7f19ff2ff567e351552ef7
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