Instructions to use utter-project/mHuBERT-147 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use utter-project/mHuBERT-147 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="utter-project/mHuBERT-147")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("utter-project/mHuBERT-147") model = AutoModel.from_pretrained("utter-project/mHuBERT-147") - Inference
- Notebooks
- Google Colab
- Kaggle
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# Languages and Datasets
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For ASR/ST/TTS datasets, only train set is used.
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* [Aishell](https://www.openslr.org/33/) and [AISHELL-3](https://www.openslr.org/93/)
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* [BibleTTS](https://www.openslr.org/129/)
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* [ClovaCall](https://github.com/clovaai/ClovaCall)
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# Languages and Datasets
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**Datasets:** For ASR/ST/TTS datasets, only train set is used.
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* [Aishell](https://www.openslr.org/33/) and [AISHELL-3](https://www.openslr.org/93/)
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* [BibleTTS](https://www.openslr.org/129/)
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* [ClovaCall](https://github.com/clovaai/ClovaCall)
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