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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 18302823470cc5a7adff95e2b7bfa3963d80fbd2e81e2ac8fca6f92603c001fb
- Size of remote file:
- 321 kB
- SHA256:
- 6825b9a91cf620bf32916ae9e4d5fb316ca6835408a03b14d803b65a1014bd46
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