Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use agercas/whisper-tiny-us with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agercas/whisper-tiny-us with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="agercas/whisper-tiny-us")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("agercas/whisper-tiny-us") model = AutoModelForSpeechSeq2Seq.from_pretrained("agercas/whisper-tiny-us") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
runs/Jul09_15-34-41_f2272acf5ab3/events.out.tfevents.1688916886.f2272acf5ab3.14209.0
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