Instructions to use GetmanY1/wav2vec2-base-fi-150k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GetmanY1/wav2vec2-base-fi-150k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GetmanY1/wav2vec2-base-fi-150k")# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("GetmanY1/wav2vec2-base-fi-150k") model = AutoModelForPreTraining.from_pretrained("GetmanY1/wav2vec2-base-fi-150k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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If you use our models or scripts, please cite our article as:
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```bibtex
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@inproceedings{
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Stymne, Sara",
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booktitle = "Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)",
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month = mar,
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year = "2025",
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address = "Tallinn, Estonia",
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publisher = "University of Tartu Library",
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url = "https://aclanthology.org/2025.nodalida-1.19/",
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pages = "192--200",
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ISBN = "978-9908-53-109-0"
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}
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```
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## Team Members
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If you use our models or scripts, please cite our article as:
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```bibtex
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@inproceedings{getman25_interspeech,
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title = {{Is your model big enough? Training and interpreting large-scale monolingual speech foundation models}},
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author = {{Yaroslav Getman and Tam谩s Gr贸sz and Tommi Lehtonen and Mikko Kurimo}},
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year = {{2025}},
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booktitle = {{Interspeech 2025}},
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pages = {{231--235}},
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doi = {{10.21437/Interspeech.2025-46}},
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issn = {{2958-1796}},
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}
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```
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## Team Members
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