Instructions to use hf-internal-testing/tiny-random-LevitModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LevitModel 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-LevitModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-LevitModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-LevitModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6783f802d495e2394a4946fe554724ffd689124512996827e333bef082ee3700
- Size of remote file:
- 28.2 MB
- SHA256:
- 96648c44d3a63e4b44e64850da25799dfa33716070728edd277beefa17702d2d
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