Instructions to use Bisher/wav2vec2-xls-r-300m-IqraEval-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bisher/wav2vec2-xls-r-300m-IqraEval-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Bisher/wav2vec2-xls-r-300m-IqraEval-3")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Bisher/wav2vec2-xls-r-300m-IqraEval-3") model = AutoModelForCTC.from_pretrained("Bisher/wav2vec2-xls-r-300m-IqraEval-3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0900ad95c8250b16a212344defd9c2ad8eea28216ff8947bb937bb65dacf794
- Size of remote file:
- 1.26 GB
- SHA256:
- 68d8c4dadd0fc2e0441d18d9f0d517eae0474b881bc141e243a8739d805d7521
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