Instructions to use kul-speech-lab/wav2vec2-xls-r-2b-lay10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kul-speech-lab/wav2vec2-xls-r-2b-lay10 with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("kul-speech-lab/wav2vec2-xls-r-2b-lay10") model = AutoModelForPreTraining.from_pretrained("kul-speech-lab/wav2vec2-xls-r-2b-lay10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2600aacf52207b410069c197db82cbe15b26b8c3999d16680b5e3655ce73c7dc
- Size of remote file:
- 2.09 GB
- SHA256:
- 0a3bd5e7aad1a2f2588447d7828458aa41517dcb8c6d4f14e0a4a40c1a5e9455
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