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:
- 51b4fc5c7a443ef49fcdd3c380bab7401b56be7eef97f99afd87d0fcdc743e8e
- Size of remote file:
- 240 kB
- SHA256:
- cd53f0a2d4e0912c69240655d96c2706de8a024fb524b10762bb816125f414b2
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