Automatic Speech Recognition
Transformers
PyTorch
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use jstoone/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jstoone/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jstoone/whisper-tiny-en")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("jstoone/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("jstoone/whisper-tiny-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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👷♀️ Fix WER display value to be zero-based percentage.
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End of training
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Training in progress, step 4000
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initial commit
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