Instructions to use iamtarun/wav2vec-osr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iamtarun/wav2vec-osr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="iamtarun/wav2vec-osr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("iamtarun/wav2vec-osr") model = AutoModelForCTC.from_pretrained("iamtarun/wav2vec-osr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd3bfc6b52be236ca24a510be4d7dbe837f91c4ac1d1c13b048a78b8af606867
- Size of remote file:
- 378 MB
- SHA256:
- 3a7577389e8719a1ec15c9a451fbc6eda94f299161298701e0551065a75f667a
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