Instructions to use seba3y/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seba3y/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="seba3y/whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("seba3y/whisper-tiny") model = AutoModelForAudioClassification.from_pretrained("seba3y/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1945c8d2ce9bd07e2f4890a6a76dd953eda35572c733531a5ca1e23cb51f70d7
- Size of remote file:
- 31.4 MB
- SHA256:
- e21776a982e44b2f48181b089187a654fb45ac0e2a525d9b41a745daf7805c60
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