Instructions to use hf-tiny-model-private/tiny-random-ASTModel 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-ASTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-ASTModel")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("hf-tiny-model-private/tiny-random-ASTModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ASTModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76758eefb64add0cae6ab8e6d511570ec0a1a628dbd3ada92c28440a91e59f0f
- Size of remote file:
- 177 kB
- SHA256:
- 0d6565e5c7fa19b3eed53506093ac79d833a5572113608810d00474794c22a00
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