Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Polish
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use bardsai/whisper-large-v2-pl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bardsai/whisper-large-v2-pl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bardsai/whisper-large-v2-pl")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bardsai/whisper-large-v2-pl") model = AutoModelForSpeechSeq2Seq.from_pretrained("bardsai/whisper-large-v2-pl") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 051cbc3f047153f9d407c3f6dd92ffd5a43c041888e4f79f98691ec3bf81f637
- Size of remote file:
- 6.17 GB
- SHA256:
- 54a296733ce7e544ab165acba6af11b10c8d54460ac0c36391fe4b511129875c
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