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:
- 7656e7394abacd9508ffe0bc6736a375ab06b7fd72f3d2e47df5de6fab131fb2
- Size of remote file:
- 3.5 kB
- SHA256:
- adc3f5cc084dc1fd10d7c135f568e4639910eaff90948d962480ec3465403271
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