Automatic Speech Recognition
Transformers
PyTorch
Ukrainian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use arampacha/whisper-large-uk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arampacha/whisper-large-uk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="arampacha/whisper-large-uk")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("arampacha/whisper-large-uk") model = AutoModelForSpeechSeq2Seq.from_pretrained("arampacha/whisper-large-uk") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a17dae704719eda4b36d3a68c82d91cbb61790c51635b57d5f45515ef9913394
- Size of remote file:
- 6.17 GB
- SHA256:
- 3ceb31809ecb155646c79bbab029514b7c7b859da33df98c2fe9e783eb013500
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