Instructions to use hadiqa123/XLS-R_timit_en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hadiqa123/XLS-R_timit_en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hadiqa123/XLS-R_timit_en")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hadiqa123/XLS-R_timit_en") model = AutoModelForCTC.from_pretrained("hadiqa123/XLS-R_timit_en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b5cd9f2f4b228418c6121938b1d7d4a103c224d013780ddfb02923e477af502
- Size of remote file:
- 1.26 GB
- SHA256:
- b85e38e412d0ebe18e82a1f2e97a554bcea4e2b693a2c9727528c40ec527852e
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