Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Hindi
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use Yocel1/whisper-small-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yocel1/whisper-small-fr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Yocel1/whisper-small-fr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Yocel1/whisper-small-fr") model = AutoModelForSpeechSeq2Seq.from_pretrained("Yocel1/whisper-small-fr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc920e19b379b5c4984c940bb99e6c9e3ee63b664970f7b0b58f80fe56083ca5
- Size of remote file:
- 967 MB
- SHA256:
- bb2bea1891a6f21c6bcce70bbb60d5fec16d4d9b5ae7bbb66492c8dab324a1ca
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