Instructions to use slplab/apac_5sents_XLS-R_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slplab/apac_5sents_XLS-R_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="slplab/apac_5sents_XLS-R_2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("slplab/apac_5sents_XLS-R_2") model = AutoModelForCTC.from_pretrained("slplab/apac_5sents_XLS-R_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f82b87e42697f2839f42018097cc471918d69f45edfe4ac3b9e027b731bec85
- Size of remote file:
- 1.26 GB
- SHA256:
- 4a4763dcb0ca4bdcb7d9f208357237a0361820df49e5e2c78bfc34916b97a178
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