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:
- d251caa52f5929a828653e1a48e550e08fd03828c1e8b13ee7e298dd8fbec1df
- Size of remote file:
- 214 kB
- SHA256:
- 87e42b248aa89320eaadb794ebc2afd1f043dcf087bb893bdd906bb7c7c12a32
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