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
Tubro?
#17
by Bidutree - opened
Hi. Are there any plans on making a KBLab version of Open AI:s Large V3 Turbo model as well? It seems to be much faster than the original Large model.
It's on a list of potential future projects to explore training either distil-whisper or whisper-turbo. We have however not started such a project yet.
Currently there's no estimate or timeline for when we might train these models, but I hope we will have the time and resources to do so.