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:
- a9e8c450537124a8cd71a44ac1252489be656ad732f0979aa6aa4e02fd8ad361
- Size of remote file:
- 3.9 kB
- SHA256:
- 0fac3a3ec662f345fa1234489e6bf31e2ad628ad98dc786e8791abca31d689f1
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