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:
- 01c923ae63f5ebcf962b70e76cdd80c9d519285b651bd4e27a51e23636552b68
- Size of remote file:
- 321 kB
- SHA256:
- 33df9970cf6e84868c489dce8470158fe152f578924667c28ec0c428b2b3c50e
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