Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use sgangireddy/whisper-medium-mls-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgangireddy/whisper-medium-mls-fr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sgangireddy/whisper-medium-mls-fr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sgangireddy/whisper-medium-mls-fr") model = AutoModelForSpeechSeq2Seq.from_pretrained("sgangireddy/whisper-medium-mls-fr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 552948705be9a62f15549e6fb71d6803dcf55fb378ea443a131b2abaf8e123f8
- Size of remote file:
- 3.79 GB
- SHA256:
- 9981afe93a9d533adea0ebff9943375953d475f9326b6aa5de1d01427301dba4
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