Instructions to use slplab/5sents_XLS-R_2_e-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slplab/5sents_XLS-R_2_e-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="slplab/5sents_XLS-R_2_e-4")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("slplab/5sents_XLS-R_2_e-4") model = AutoModelForCTC.from_pretrained("slplab/5sents_XLS-R_2_e-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 408ac5281531e51b65545d5e8481a5f7eee81bcd3d0933bfea24a36d66cc42e7
- Size of remote file:
- 1.26 GB
- SHA256:
- 0d64bbfdf51f142d108da46eb2d27ed9e3e7a370a8480bad98e97ae439132bb9
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