Instructions to use jonik/w2v2-libri-10min with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonik/w2v2-libri-10min with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonik/w2v2-libri-10min")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonik/w2v2-libri-10min") model = AutoModelForCTC.from_pretrained("jonik/w2v2-libri-10min", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9566dda2ec5f540911b3b7aed6d6ad53ed3c6d271fd5cdda390ce90b1a704a7
- Size of remote file:
- 378 MB
- SHA256:
- 7c088e85b1be0337bd03a159c88fdd9d78956611fe77a73aafce28f0b979b03d
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