Instructions to use hf-internal-testing/tiny-random-DinatModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DinatModel 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-DinatModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-DinatModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-DinatModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ffc373c80006c7cf6cbd8c86026c8e6da63c8eb20bc5464b85cda07366c9156
- Size of remote file:
- 321 kB
- SHA256:
- 664c81f09b1efb7a534ccb7046da4e1a0e58132b2f1bcbaf259ad92e5b7b5484
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