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:
- 44bc842dc406f12fa572cd26425002ac30abdf76a2d3defcbdc30810b23814b7
- Size of remote file:
- 28.3 MB
- SHA256:
- 5ec6d55586656e3d4477ac69c8c867e2496056fc7ed8a298f04f93253731dcba
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