Instructions to use KBLab/kb-whisper-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KBLab/kb-whisper-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="KBLab/kb-whisper-large")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("KBLab/kb-whisper-large") model = AutoModelForSpeechSeq2Seq.from_pretrained("KBLab/kb-whisper-large") - Notebooks
- Google Colab
- Kaggle
Common Voice - evalution dataset
#11
by solailabs - opened
Excellent work! Did you use the entire Common Voice SW - as a evaluation dataset, or did you only test subset of it ?
Hi, thank you. We used the whole CV 16.1 for the evaluation. More detailed information can be found in https://arxiv.org/abs/2505.17538 .
Lauler changed discussion status to closed