Evaluating small neural networks for general-purpose lossy data compression
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Tibo De Peuter 59722acf76
fix: Transformer Optuna params
Co-authored-by: Robin Meersman <echteenrobin@gmail.com>
2025-12-07 20:45:29 +01:00
src fix: Transformer Optuna params 2025-12-07 20:45:29 +01:00
.gitignore fix: Ignore saved models 2025-12-05 11:01:15 +01:00
.python-version chore: Change versions, setup HPC 2025-11-30 16:51:44 +01:00
job.pbs chore: Also add datapaths to job 2025-11-30 21:58:57 +01:00
main.py feat: Add model choice 2025-12-06 21:55:35 +01:00
pyproject.toml fix: Readd matplotlib 2025-11-30 19:27:35 +01:00
README.md Streamline datasets 2025-12-04 23:13:16 +01:00
uv.lock fix: Readd matplotlib 2025-11-30 19:27:35 +01:00

neural compression

Example usage:

python main_cnn.py --debug train --dataset enwik9 --method optuna

Running locally

uv sync --all-extras

Running on the Ghent University HPC

See the Infrastructure docs for more information about the clusters.

module swap cluster/joltik # Specify the (GPU) cluster, {joltik,accelgor,litleo}

qsub job.pbs               # Submit job
qstat                      # Check status