Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Hindi
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use arbml/whisper-tiny-ar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arbml/whisper-tiny-ar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="arbml/whisper-tiny-ar")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("arbml/whisper-tiny-ar") model = AutoModelForSpeechSeq2Seq.from_pretrained("arbml/whisper-tiny-ar") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16c6c08f48e62d9caa7a0d03185433edda7e2b70562ed82d259562b2cc8a7661
- Size of remote file:
- 151 MB
- SHA256:
- cfc4bd0136ea05e061b23aa0745b0c1f336b160838f34fd71a2bc4711fe46de2
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