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:
- 72857f7cf192787f8ccfa276ae5a76b37498fffe830532f61a442c0b7fa7e263
- Size of remote file:
- 214 kB
- SHA256:
- 278ceddacd83dca4503ece63f4e2977a917a1d46495f9e4c5475a74c81b58ad6
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