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:
- c55230f899851c0ffe9e4b60f6a03d2b4ced2354c7ce2d50ab43fb4ced52542d
- Size of remote file:
- 3.71 kB
- SHA256:
- f030af79d4c75c5dbc044b3cf8b54bdcc802f4bddd60d2a0ad2e0c0592d18741
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