Instructions to use IABDs8a/whisper-tiny-top3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IABDs8a/whisper-tiny-top3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="IABDs8a/whisper-tiny-top3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("IABDs8a/whisper-tiny-top3") model = AutoModelForSpeechSeq2Seq.from_pretrained("IABDs8a/whisper-tiny-top3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- daca2ffdfa93caa5a0c63ba7cdd9d32d7ee28e523bfd70af6b8b3f472e227d5b
- Size of remote file:
- 151 MB
- SHA256:
- 643a1a4ad503fabdabe6c851c97d899881019ce9025ee0cc6f5e2b24bf01b8aa
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