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:
- 992b8bfe36be9bf6b97ebfcc350c08c30ce1a74fa6ecd5f6d458ab85a931d9c9
- Size of remote file:
- 321 kB
- SHA256:
- 723159abf8b8f8c0e45afbbea5ffbc75bd2d7a0a34c16112e0d16caf617c3892
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