Instructions to use hf-tiny-model-private/tiny-random-UniSpeechForPreTraining 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-UniSpeechForPreTraining with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechForPreTraining") model = AutoModelForPreTraining.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechForPreTraining") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bcbc658ab72f923fb371011dc5ec3d32b40eb67ffe2fee7309ea62ee3f77ffcd
- Size of remote file:
- 833 kB
- SHA256:
- b76ae771651b74cb5317a0200b6b3e8f49c927a1d1abaea7c158d8c8e829cc24
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