Automatic Speech Recognition
Transformers
PyTorch
Urdu
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use testphase73/whisper-large-ur with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use testphase73/whisper-large-ur with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="testphase73/whisper-large-ur")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("testphase73/whisper-large-ur") model = AutoModelForSpeechSeq2Seq.from_pretrained("testphase73/whisper-large-ur") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cec5b9c5523013e7e32baa2caf1ecd9df99827cc64c1411ec80cc0734e398266
- Size of remote file:
- 302 MB
- SHA256:
- 588aead1b85a3f4aaaa076e2e50781804743382d717a622ff4e1c0d7180855a9
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