Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Arabic
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use MohammedNasri/WHISPER-LARGE-ARABIC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MohammedNasri/WHISPER-LARGE-ARABIC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="MohammedNasri/WHISPER-LARGE-ARABIC")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("MohammedNasri/WHISPER-LARGE-ARABIC") model = AutoModelForSpeechSeq2Seq.from_pretrained("MohammedNasri/WHISPER-LARGE-ARABIC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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1
Parent(s): 6ff74c4
End of training
Browse files
README.md
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dataset:
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name: Common Voice 11.0
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type: mozilla-foundation/common_voice_11_0
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config:
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split: test
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args: 'config: ar, split: test'
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metrics:
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dataset:
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name: Common Voice 11.0
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type: mozilla-foundation/common_voice_11_0
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config: ar
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split: test
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args: 'config: ar, split: test'
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metrics:
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