Instructions to use hf-internal-testing/tiny-random-EncodecModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-EncodecModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-EncodecModel")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-EncodecModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-EncodecModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 254856c8f8697d04fe1252a69cbf39d04dc2e54fdb8f4fb59720b4e7459c0c83
- Size of remote file:
- 93.1 MB
- SHA256:
- 2f6f5e77680f49f4fc9e0e665ccd65e9112ac4e18e2ce681c66f6373e350fbb4
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