Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Italian
wav2vec2
audio
speech
phonemize
phoneme
Eval Results (legacy)
Instructions to use Cnam-LMSSC/wav2vec2-italian-phonemizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cnam-LMSSC/wav2vec2-italian-phonemizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Cnam-LMSSC/wav2vec2-italian-phonemizer")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Cnam-LMSSC/wav2vec2-italian-phonemizer") model = AutoModelForCTC.from_pretrained("Cnam-LMSSC/wav2vec2-italian-phonemizer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f95bdb4f83686e7935f120044984685e5ba7c9f5cbbba698ef4de0c4ea50e5c6
- Size of remote file:
- 378 MB
- SHA256:
- 62f1eb8a6d8ffee497ceb21fb24889ff0b84b2d5137f876eebc2fbb45f956e59
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