Instructions to use hugo-vanhamme/w2v2-libri with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hugo-vanhamme/w2v2-libri with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hugo-vanhamme/w2v2-libri")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hugo-vanhamme/w2v2-libri") model = AutoModelForCTC.from_pretrained("hugo-vanhamme/w2v2-libri", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed5f6113339740e743dd776537846d45597249ff750de5532fded959ea9aa466
- Size of remote file:
- 378 MB
- SHA256:
- 950344fa7f82cc42ccab62974246deb75f27186eda95dc0cd2fd75641b6172f1
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