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:
- 23926f15b2bb83e3b497e2240e4e8a38b34e0b946cb5a445984e1298ec26c73e
- Size of remote file:
- 5.84 kB
- SHA256:
- 4951d0e01eeb08400d8298e929ec991e5388e1c669b8429cccf35cd379c1d31d
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