Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Polish
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use bardsai/whisper-large-v2-pl-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bardsai/whisper-large-v2-pl-v2 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-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bardsai/whisper-large-v2-pl-v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("bardsai/whisper-large-v2-pl-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add Apache 2.0 license
#5
by NorbertRop - opened
The model card had no license, unlike its base model bardsai/whisper-large-v2-pl (Apache 2.0). Adds license: apache-2.0 and base_model to the metadata, the LICENSE file, and a License section crediting the training data: Common Voice 11.0 (CC0 1.0) and FLEURS (CC BY 4.0).
NorbertRop changed pull request status to merged