Instructions to use bookbot/wav2vec2-xls-r-300m-swahili-cv-fleurs-alffa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bookbot/wav2vec2-xls-r-300m-swahili-cv-fleurs-alffa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bookbot/wav2vec2-xls-r-300m-swahili-cv-fleurs-alffa")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("bookbot/wav2vec2-xls-r-300m-swahili-cv-fleurs-alffa") model = AutoModelForCTC.from_pretrained("bookbot/wav2vec2-xls-r-300m-swahili-cv-fleurs-alffa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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