Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use ruisp/whisper-tiny-ft-polyai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruisp/whisper-tiny-ft-polyai with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ruisp/whisper-tiny-ft-polyai")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ruisp/whisper-tiny-ft-polyai") model = AutoModelForSpeechSeq2Seq.from_pretrained("ruisp/whisper-tiny-ft-polyai", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 242c3b72aafd6f2cc57cae82419ea5e6ec27f1d4bdbbb1c1632c12dca041f59c
- Size of remote file:
- 4.16 kB
- SHA256:
- 7b85014998a2523bedeb61787308c3fa23aaab284ca466ec274c9c4b74c19c71
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