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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("utter-project/mHuBERT-147") model = AutoModel.from_pretrained("utter-project/mHuBERT-147", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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**This repository contains the best mHuBERT-147 pre-trained model.**
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**ATTENTION: THERE IS CURRENTLY A LOADING ERROR ON HUGGINGFACE. PLEASE USE torch<=2 FOR LOADING THE MODEL!**
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**MODEL DETAILS:** 3rd iteration, K=1000, HuBERT base architecture (95M parameters), 147 languages.
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# Table of Contents:
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**This repository contains the best mHuBERT-147 pre-trained model.**
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**MODEL DETAILS:** 3rd iteration, K=1000, HuBERT base architecture (95M parameters), 147 languages.
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# Table of Contents:
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