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:
- 9bcd5f68a76e4d6bc3d32916744482f73072db9b1563d377464e990cf9aae05c
- Size of remote file:
- 151 MB
- SHA256:
- dfc7b88db998fc426b52f4c00bfa7934d8046fb0cdf0720281461f6f43cc45fc
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