Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
whisper-event
Generated from Trainer
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use arbml/whisper-largev2-ar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arbml/whisper-largev2-ar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="arbml/whisper-largev2-ar")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("arbml/whisper-largev2-ar") model = AutoModelForSpeechSeq2Seq.from_pretrained("arbml/whisper-largev2-ar") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9054e829ed788fe1dda27f7f3c61b130658467cc00c8fb91a29fdb968e99b65d
- Size of remote file:
- 4.67 kB
- SHA256:
- 479d28020bd7b0e5b3bd937befbcdc9b89bedfd2c7ba3c9b4b54a05384fee311
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