Instructions to use Isma/afrispeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isma/afrispeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Isma/afrispeech")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Isma/afrispeech") model = AutoModelForCTC.from_pretrained("Isma/afrispeech") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37f253d8921d847f511600d1aadfcba229fe1307e833d97219edb879b7adb06a
- Size of remote file:
- 378 MB
- SHA256:
- c6d5958c10ab934b184a2693db2c1d66f44e28fd67e72c6f6d70fa1bbfeecd1f
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