Instructions to use SiRoZaRuPa/japanese-HuBERT-base-VADLess-ASR-RSm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SiRoZaRuPa/japanese-HuBERT-base-VADLess-ASR-RSm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SiRoZaRuPa/japanese-HuBERT-base-VADLess-ASR-RSm")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("SiRoZaRuPa/japanese-HuBERT-base-VADLess-ASR-RSm") model = AutoModelForCTC.from_pretrained("SiRoZaRuPa/japanese-HuBERT-base-VADLess-ASR-RSm") - Notebooks
- Google Colab
- Kaggle