Instructions to use hf-tiny-model-private/tiny-random-YolosModel 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-YolosModel 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-YolosModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-YolosModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-YolosModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9af763e90abe4c43a4be431ae3c1b3664f14c4f75809bd1da416654d48d7603
- Size of remote file:
- 323 kB
- SHA256:
- 63ef178841f0ae93fc310202b0d0bf3cbd35496f6ca13c90ca176d5e0d6a91fc
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