Instructions to use nrshoudi/wav2vec_arabic_mdd_experiment2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nrshoudi/wav2vec_arabic_mdd_experiment2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nrshoudi/wav2vec_arabic_mdd_experiment2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("nrshoudi/wav2vec_arabic_mdd_experiment2") model = AutoModelForCTC.from_pretrained("nrshoudi/wav2vec_arabic_mdd_experiment2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b6ef157f3f8e73526e8343fe2c85a61d2bd9ebade9237de863f9eec7280c79a
- Size of remote file:
- 1.26 GB
- SHA256:
- dcf5789852b1c64d927d9ec6ebc9178a88a26a542469c05e94621b17319abdb0
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