Instructions to use hf-internal-testing/tiny-random-RegNetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RegNetModel 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-RegNetModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-RegNetModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-RegNetModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5df9e0fa91c489e6c62d4cd11d4e18cd4d2bc293beb1ced1e2077c1db28d6b0
- Size of remote file:
- 339 kB
- SHA256:
- 2e6e3811aa7145ef22055ecc3db307a3522a637b73f3166443cee2602f6d8d3d
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