Instructions to use nrshoudi/wav2vec2-large-xls-r-300m-Arabic-phoneme-based-MDD-experiment3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nrshoudi/wav2vec2-large-xls-r-300m-Arabic-phoneme-based-MDD-experiment3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nrshoudi/wav2vec2-large-xls-r-300m-Arabic-phoneme-based-MDD-experiment3")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("nrshoudi/wav2vec2-large-xls-r-300m-Arabic-phoneme-based-MDD-experiment3") model = AutoModelForCTC.from_pretrained("nrshoudi/wav2vec2-large-xls-r-300m-Arabic-phoneme-based-MDD-experiment3", device_map="auto") - Notebooks
- Google Colab
- Kaggle