Instructions to use elgeish/wav2vec2-large-xlsr-53-levantine-arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use elgeish/wav2vec2-large-xlsr-53-levantine-arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="elgeish/wav2vec2-large-xlsr-53-levantine-arabic")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("elgeish/wav2vec2-large-xlsr-53-levantine-arabic") model = AutoModelForCTC.from_pretrained("elgeish/wav2vec2-large-xlsr-53-levantine-arabic") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d39988973bcf31a03ccc648609b686ef8c551de69c22ebb03ab3d19a8232d20d
- Size of remote file:
- 1.26 GB
- SHA256:
- 670c925f7ff79306cfa38b85b3759046c62101fb375b5f23a95078ead7c88a5f
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