Instructions to use StephennFernandes/wav2vec2-XLS-R-300m-konkani with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StephennFernandes/wav2vec2-XLS-R-300m-konkani with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="StephennFernandes/wav2vec2-XLS-R-300m-konkani")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("StephennFernandes/wav2vec2-XLS-R-300m-konkani") model = AutoModelForCTC.from_pretrained("StephennFernandes/wav2vec2-XLS-R-300m-konkani") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56a0955079a61d52e0b14d402b4448dafb09307dfe8d19e5b6008cc5bfbd6cd6
- Size of remote file:
- 1.26 GB
- SHA256:
- 9cc9dc511453f4ec6e5ce4322bc53a8716c7b200d9f8051ceec31ef697110bc5
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