Instructions to use bgstud/whisper-tiny-libri with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bgstud/whisper-tiny-libri with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bgstud/whisper-tiny-libri")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bgstud/whisper-tiny-libri") model = AutoModelForSpeechSeq2Seq.from_pretrained("bgstud/whisper-tiny-libri") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 087f4739ba1f11542410fe528e5456b26aaa8c7d8d84617a8551f3a73cf7d0f9
- Size of remote file:
- 151 MB
- SHA256:
- 5e2b55ca9400001cdf5a08b66f017b9df096cef63b5235d5054b1773d6cfbe7c
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