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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- efbe8976f6ae2d31b38e56dc117bb910bde9fbd146121d846efaf36b0eb9d488
- Size of remote file:
- 93.2 MB
- SHA256:
- 21c1427ca1fb390abec67f58e3b2eaa9047300610674570ff59935b6c4a1bcdd
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