Instructions to use hf-internal-testing/tiny-random-unispeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-unispeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-unispeech")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-unispeech") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-unispeech") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db9eea13bc2f6f77e12c8ce0eb602c21f968cfd8525fa5834cb59f86e1ce48e7
- Size of remote file:
- 159 kB
- SHA256:
- d713e283c3fe7d58396361fa8f45320351951f4d3755fd1b3c45b15a480d1458
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