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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 874b92d54a6d98d5d53defeca03169072476363c9d1d6f03298f8cbfe97b5d22
- Size of remote file:
- 3.64 kB
- SHA256:
- 657162908d2af93b83e9b1991dbcc0276d1a4f9501a37af0e6f68cc2fcc01efd
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