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
- Xet hash:
- 1bf001f2473e3ee4344fdf06585e322f2c2e7885f9cf2e166f3bcf8ec907a2af
- Size of remote file:
- 3.77 kB
- SHA256:
- 0ccd147712d75b954c1a8d933003f24e6f20067f560cc189c5df99357385d0d7
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