Instructions to use hf-tiny-model-private/tiny-random-LevitModel 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-LevitModel 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-LevitModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-LevitModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-LevitModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c52b6ce6d566be581dcd1e9ebcb5400087e6dd0621df7bf0f408a1be97288144
- Size of remote file:
- 28.2 MB
- SHA256:
- 96fd7a2011514efba1f79cbff6b392c5f9a4541904d0db48608068cc6a1e9365
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