Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
whisper-event
Generated from Trainer
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use arbml/whisper-small-ar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arbml/whisper-small-ar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="arbml/whisper-small-ar")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("arbml/whisper-small-ar") model = AutoModelForSpeechSeq2Seq.from_pretrained("arbml/whisper-small-ar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4d72e60f864bcd8fb340eecbe3c069b52b6739dd0aa449685ed879894ba619f
- Size of remote file:
- 967 MB
- SHA256:
- e3fb067a2660ca67ebacd712af1ffbb31ad00583a3f08ae7a68ee7373b5de967
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