_____ ______ __ __ ______ _____ ______ __ __ __ __
/\ __-. /\ __ \ /\ "-./ \ /\ ___\ /\ __-. /\ ___\ /\ \/\ \ /\ "-./ \
\ \ \/\ \\ \ __ \\ \ \-./\ \\ \ __\ \ \ \/\ \\ \___ \\ \ \_\ \\ \ \-./\ \
\ \____- \ \_\ \_\\ \_\ \ \_\\ \_____\\ \____- \/\_____\\ \_____\\ \_\ \ \_\
\/____/ \/_/\/_/ \/_/ \/_/ \/_____/ \/____/ \/_____/ \/_____/ \/_/ \/_/
Model description
This repository contains a model for Danish abstractive summarisation of medicaltext.
This model is a fine-tuned version of DanSumT5-base trained on a danish medical text dataset.
The model was trained on LUMI using 1 AMD MI250X GPU.
Authors
Nicolaj Larsen
Mikkel Kildeberg
Emil Schledermann
Framework versions
- Transformers 4.30.2
- Pytorch 1.12.1+git7548e2f
- Datasets 2.13.2
- Tokenizers 0.13.3
- Downloads last month
- 39