Instructions to use facebook/mms-1b-all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mms-1b-all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/mms-1b-all")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("facebook/mms-1b-all") model = AutoModelForCTC.from_pretrained("facebook/mms-1b-all", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c686181b76907015901aeb24260fc0ae60940f3f99dcd7c541625daaf7334625
- Size of remote file:
- 8.91 MB
- SHA256:
- f1c557771eb22ab0289e1ba9b0cbf3d5fcf96b78560fdf0293ac874f6a5991cb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.