Instructions to use lsnoo/XLS-R-300m_kspon_jamo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lsnoo/XLS-R-300m_kspon_jamo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lsnoo/XLS-R-300m_kspon_jamo")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lsnoo/XLS-R-300m_kspon_jamo") model = AutoModelForCTC.from_pretrained("lsnoo/XLS-R-300m_kspon_jamo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac1cca3f81b0e544b4ac6463604fc81bc4938e2e6fa147bca58b2526f827fce0
- Size of remote file:
- 1.26 GB
- SHA256:
- b7ccd054fa5a9fd3772fc6dff3805e3b1d27edab88144b92a615a2ca03d5c6e3
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