Public code for Macquarie University's contribution to BioASQ 10 Synergy.
If you use this code, please cite the following paper:
D. Mollá (2022). Query-Focused Extractive Summarisation for Biomedical and COVID-19 Question Answering. CLEF2022 Working Notes.
Besides the files available in this repository, you need to obtain the following file. It is not in the github repository because of the large size:
- task10b_distilbert_model_32.pt (254MB) (please contact diego.molla-aliod@mq.edu.au)
The following code replicates the results of runs MQ1 and MQ2 at round 4.
$ conda env create -f environment.yml
$ conda activate bioasq10-synergy
$ conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch
(bioasq8-synergy) $ python run_mq1.py
(bioasq8-synergy) $ python run_mq2.py