Instructions to use StofEzz/whisper-tiny-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StofEzz/whisper-tiny-fr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="StofEzz/whisper-tiny-fr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("StofEzz/whisper-tiny-fr") model = AutoModelForSpeechSeq2Seq.from_pretrained("StofEzz/whisper-tiny-fr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb5b03f8a67f15e1c36a6069a36d6a990124c2c9e35dd604da71c713b32a3dc5
- Size of remote file:
- 151 MB
- SHA256:
- 44045347834eb23079168b2965d187ce7ab128f9532d80ee883fe9b600677557
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