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:
- 65ec9b7e113f80c158b52c86d9fdb824c7c809737743c6e8373b060e14ff9b49
- Size of remote file:
- 158 kB
- SHA256:
- 593fa364c253db25bcd3ae504cf99016d65796502d726f51869ec7e7998bd645
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