Instructions to use hf-tiny-model-private/tiny-random-RegNetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-RegNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-RegNetModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-RegNetModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-RegNetModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9b7505e9136c7399c29f6cf66f98f247595049fe9b85c3ef73a66c581488d9a
- Size of remote file:
- 339 kB
- SHA256:
- 3edb1667b4863fdae092b97bcbfb2782e657da2e07a188b36ace68222168064a
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