Instructions to use cminja/whisper-tiny-sr-commonvoice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cminja/whisper-tiny-sr-commonvoice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="cminja/whisper-tiny-sr-commonvoice")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("cminja/whisper-tiny-sr-commonvoice") model = AutoModelForSpeechSeq2Seq.from_pretrained("cminja/whisper-tiny-sr-commonvoice") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1bb671001e91bbe1d6d8e2207555c60366d507c7fb3ff972628298ebc161ad95
- Size of remote file:
- 5.3 kB
- SHA256:
- a5545161fe7c3fe6281cdee4b4c79b538acb97f4f467f4fa884467bb5025d650
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