Instructions to use Alvin-Nahabwe/mms-1b-all-Sagalee-orm-85hrs-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alvin-Nahabwe/mms-1b-all-Sagalee-orm-85hrs-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Alvin-Nahabwe/mms-1b-all-Sagalee-orm-85hrs-4")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Alvin-Nahabwe/mms-1b-all-Sagalee-orm-85hrs-4") model = AutoModelForCTC.from_pretrained("Alvin-Nahabwe/mms-1b-all-Sagalee-orm-85hrs-4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ade418ffafadf1ab1f4681ecfb761d4a436938ff9f05b32da5a59fed0b26e9b
- Size of remote file:
- 5.37 kB
- SHA256:
- 1f6b681a4b53f15cc5d33876414002e43f98fa9202f51aa25167f54e60f41ccd
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