Automatic Speech Recognition
Transformers
PyTorch
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use marma/whisper-tiny-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marma/whisper-tiny-sv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="marma/whisper-tiny-sv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("marma/whisper-tiny-sv") model = AutoModelForSpeechSeq2Seq.from_pretrained("marma/whisper-tiny-sv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61eec76ae3b47479e27890597c1adc1dbdddaa22cc03c178e1a1b25961b4f141
- Size of remote file:
- 151 MB
- SHA256:
- 3860eb03cac79d73ef4f656a0eb0e7571429bfcb0da7f5ad41a8c5ba716d195c
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