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:
- 0ad71b315f6fc699b178aa67b6900a5270539ae425118163c01899c12a86693d
- Size of remote file:
- 1.06 kB
- SHA256:
- 692f3e1084eb2564164915a23c8f7e773c062c34e07aca23cf5d862d00ccbcfe
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