Instructions to use hf-internal-testing/tiny-random-UniSpeechModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UniSpeechModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-UniSpeechModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-UniSpeechModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-UniSpeechModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 979e3be57d6624cbc9bc2217903ec63db9fa28fcd0352e35954eb17ebd2978a5
- Size of remote file:
- 132 kB
- SHA256:
- 8d3d3be7960b78f3b5299de80a592c3501e74b7470b0440c6fd3765bce8b38e8
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