Instructions to use ramimmo/wav2vec2phoneme with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ramimmo/wav2vec2phoneme with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ramimmo/wav2vec2phoneme")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ramimmo/wav2vec2phoneme") model = AutoModelForCTC.from_pretrained("ramimmo/wav2vec2phoneme", device_map="auto") - Notebooks
- Google Colab
- Kaggle
License
#2
by mrfakename - opened
Hi,
This model looks really cool, and I was wondering if you might be able to add a license (preferably permissive, ie MIT/Apache) to it so we can incorporate it into our code.
Thank you!