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:
- 4f9c839dc933cd3c4650434a7cb060abc5f097bbabc110023c0d0e836959fb54
- Size of remote file:
- 28.3 MB
- SHA256:
- 3aa581ddf547398f580059448798f5018a4351b9e07090422927ed7b218f34e1
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