Automatic Speech Recognition
Transformers
Safetensors
French
wav2vec2
audio
speech
phonemize
phoneme
Eval Results (legacy)
Instructions to use Cnam-LMSSC/phonemizer_headset_microphone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cnam-LMSSC/phonemizer_headset_microphone with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Cnam-LMSSC/phonemizer_headset_microphone")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Cnam-LMSSC/phonemizer_headset_microphone") model = AutoModelForCTC.from_pretrained("Cnam-LMSSC/phonemizer_headset_microphone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
add vibravox paper on arXiV
Verified signatureaa608ae
-
Update README.md
Verified signatureba6fee5
-
Update README.md
Verified signature413775b -
Update README.md
Verified signatureed2528a -
Update README.md
Verified signaturedc51645 -
Update README.md
Verified signatureb1b3e70 -
Upload standard Wav2Vec2Processor
Verified signatureb89c471 -
Upload Wav2Vec2ForCTC after 10 epochs
Verified signature40b14c8 -
initial commit
Verified signature75654a7