Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
English
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use J3/whisper-tiny-en-US with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use J3/whisper-tiny-en-US with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="J3/whisper-tiny-en-US")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("J3/whisper-tiny-en-US") model = AutoModelForSpeechSeq2Seq.from_pretrained("J3/whisper-tiny-en-US", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
runs/Jul08_12-27-35_bf11e3653e08/events.out.tfevents.1688819315.bf11e3653e08.528.0
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