Instructions to use oluwagbotty/mms_eng_yor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oluwagbotty/mms_eng_yor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="oluwagbotty/mms_eng_yor")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("oluwagbotty/mms_eng_yor") model = AutoModelForCTC.from_pretrained("oluwagbotty/mms_eng_yor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9650aeeb1bf5e87ee52e1a17d06c30b3ab4d64e0d67586b05be0d7f05f5f5110
- Size of remote file:
- 988 Bytes
- SHA256:
- e68868f950ff3571f61e8d11f5c03814199d470897fcc79cf29e5d0290c3aebb
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