Instructions to use antony66/whisper-large-v3-russian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use antony66/whisper-large-v3-russian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="antony66/whisper-large-v3-russian")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("antony66/whisper-large-v3-russian") model = AutoModelForSpeechSeq2Seq.from_pretrained("antony66/whisper-large-v3-russian", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Improve suggestion
Hello, antony66, thanks for your contribute of this model. I am trying to improve russian whisper too. In my option, finetune on common voice will not improve much, because I think the original whisper have collect the dataset and train. I think we need some accurate dataset. Generally after finetune, the wer can reduce 50%.
This model improve much in it's dataset. I think original whisper may has not train it.
https://github.com/sovse/base_rus_whisper_stt
And original whisper may not use dataset:
https://github.com/snakers4/open_stt
Hey! Yes this is exactly my thought as well. So I had been working on a custom dataset until I had to switch to another task temporarily. Looking forward to returning to this task soon