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:
- 164e07d081ecb8449191e3548e9298daa68df2a5b0a7599833fca1350093f7f5
- Size of remote file:
- 6.17 GB
- SHA256:
- e4fedd58b5b6bc1be146c89e68498925d835033698a01cb76e9243b7246dfe31
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