Instructions to use hadiqa123/XLS-R_53_english with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hadiqa123/XLS-R_53_english with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hadiqa123/XLS-R_53_english")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hadiqa123/XLS-R_53_english") model = AutoModelForCTC.from_pretrained("hadiqa123/XLS-R_53_english") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a55f443be00e1a23babe9fc1c189de065f52728b4fe97f271bde23b222f0d5cb
- Size of remote file:
- 1.26 GB
- SHA256:
- dd80c1cbcb075891f3d4edde7606efc0be198bef0238aca025fde579c9b69ad5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.