Instructions to use KBLab/kb-whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KBLab/kb-whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="KBLab/kb-whisper-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("KBLab/kb-whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("KBLab/kb-whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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### Citation
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### Citation
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KB-Whisper is a product of KBLab of the National Library of Sweden.
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Key contributors include [Faton Rekathati](https://huggingface.co/Lauler), [Justyna Sikora](https://huggingface.co/justynasikora), [Robin Kurtz](https://huggingface.co/robinq), [Agnes Toftgård](https://huggingface.co/agnestoftgard), and [Leonora Vesterbacka](https://huggingface.co/Leonoravesterbacka), under the direction of Love Börjeson.
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Please refer to the following paper if you want to cite our work with KB-Whisper.
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[Swedish Whispers; Leveraging a Massive Speech Corpus for Swedish Speech
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Recognition](https://arxiv.org/abs/2505.17538)
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An update citation with the paper accepted by Interspeech 2025 coming soon...
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