Automatic Speech Recognition
Transformers
PyTorch
Safetensors
French
wav2vec2
audio
speech
phonemize
phoneme
Eval Results (legacy)
Instructions to use Cnam-LMSSC/wav2vec2-french-phonemizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cnam-LMSSC/wav2vec2-french-phonemizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Cnam-LMSSC/wav2vec2-french-phonemizer")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Cnam-LMSSC/wav2vec2-french-phonemizer") model = AutoModelForCTC.from_pretrained("Cnam-LMSSC/wav2vec2-french-phonemizer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 162b0a78350a7281328a09b7e857796999e3111556882b1c87cfd12392be1033
- Size of remote file:
- 378 MB
- SHA256:
- 027fe20e12fa11f6f05e179b7678b8cc61f2866ac98afa29b838a9b38f15c5ae
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