Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Sandiago21/whisper-tiny-PolyAI-minds14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sandiago21/whisper-tiny-PolyAI-minds14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sandiago21/whisper-tiny-PolyAI-minds14")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Sandiago21/whisper-tiny-PolyAI-minds14") model = AutoModelForSpeechSeq2Seq.from_pretrained("Sandiago21/whisper-tiny-PolyAI-minds14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc531c5b5bde6cb94c544d67ba970b06859e90fa8a2ae24e852b930437c6d305
- Size of remote file:
- 151 MB
- SHA256:
- 68afb6332a2a75232ea0c2c178ce5a21050ad5888362742e864e6759afa0b7f4
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