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:
- 66dde8bc10f35c0d0f18d8879030f38b6e6fc90b1bef801002d5a81e26d3dfc7
- Size of remote file:
- 1.06 kB
- SHA256:
- d31650d4c3644bd481cd700b78bed69814c2eb45b19b09ba8f6f3bb316fc3da3
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