Automatic Speech Recognition
Transformers
PyTorch
Arabic
wav2vec2
hf-asr-leaderboard
robust-speech-event
Eval Results (legacy)
Instructions to use phantomcoder1996/wav2vec2-large-xls-r-300m-arabic-colab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phantomcoder1996/wav2vec2-large-xls-r-300m-arabic-colab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="phantomcoder1996/wav2vec2-large-xls-r-300m-arabic-colab")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("phantomcoder1996/wav2vec2-large-xls-r-300m-arabic-colab") model = AutoModelForCTC.from_pretrained("phantomcoder1996/wav2vec2-large-xls-r-300m-arabic-colab") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 250082bbda15195c72d492d716e4560898ce65b18af59753ae9f7cb861f4b0ee
- Size of remote file:
- 3.06 kB
- SHA256:
- a46f773a73616244b9131212a3920438275c6aa338e20356a83c5f3ca12714c8
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