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:
- acd6dedec03cb207f62de8bbe26beecb5daedde93ecc351ffca37a88469aa7c6
- Size of remote file:
- 2.61 kB
- SHA256:
- 8d96ea3bb8c12990fc3033e3717e917a2e69392e05145af21c98f3996837104c
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