Automatic Speech Recognition
Transformers
Safetensors
French
wav2vec2
audio
speech
phonemize
phoneme
Eval Results (legacy)
Instructions to use Cnam-LMSSC/phonemizer_temple_vibration_pickup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cnam-LMSSC/phonemizer_temple_vibration_pickup with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Cnam-LMSSC/phonemizer_temple_vibration_pickup")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Cnam-LMSSC/phonemizer_temple_vibration_pickup") model = AutoModelForCTC.from_pretrained("Cnam-LMSSC/phonemizer_temple_vibration_pickup", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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