Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
French
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use M2LabOrg/whisper-small-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M2LabOrg/whisper-small-fr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="M2LabOrg/whisper-small-fr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("M2LabOrg/whisper-small-fr") model = AutoModelForSpeechSeq2Seq.from_pretrained("M2LabOrg/whisper-small-fr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5bf5ace757e9227a31f1692d37fecc7a2ad7dac4c0150b0de019ea8e7e636c88
- Size of remote file:
- 5.24 kB
- SHA256:
- ab390f4006577c558f89793496899847fa0e4c64275c41d7ba8f0bb0909e1e21
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