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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f323dd7c174b34d8930b409babb83d9db0da5dd0280dd164200e301aa60e3aa1
- Size of remote file:
- 213 kB
- SHA256:
- 15ac058728316e9e841fa42126bf230d796c849fb69a764a2d723b7e92d9324b
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