Instructions to use nrshoudi/wav2vec2-large-xls-r-300m-Arabic-phoneme-based-MDD 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 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")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("nrshoudi/wav2vec2-large-xls-r-300m-Arabic-phoneme-based-MDD") model = AutoModelForCTC.from_pretrained("nrshoudi/wav2vec2-large-xls-r-300m-Arabic-phoneme-based-MDD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a841f7cc51db24f1488dc26332584c979342874625071bd2d4a41c8b7637e033
- Size of remote file:
- 4.16 kB
- SHA256:
- 6c8553eab68db3c8b2546889f2df0d9e4c3ce80eba7d1f78cd8cfed091dcf1c6
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