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:
- e2c5c8aa4408d3f4470c286b9b2ab36c034045e0ebce1b6b564df2c31b56306f
- Size of remote file:
- 14.3 kB
- SHA256:
- 51627cd23ad6110de8b8e7c03acfa86cd0718ebf9aa35b8920b0f452ce039239
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