Instructions to use wasertech/wav2vec2-cv-fr-9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wasertech/wav2vec2-cv-fr-9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="wasertech/wav2vec2-cv-fr-9")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("wasertech/wav2vec2-cv-fr-9") model = AutoModelForCTC.from_pretrained("wasertech/wav2vec2-cv-fr-9") - Notebooks
- Google Colab
- Kaggle
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by wasertech - opened
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wasertech changed pull request status to merged