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Reproducibility scripts for the HyperTensor / Geodesic Runtime Compression (GRC) report by William Ken Ohara Stewart (NagusameCS).
This is a small companion package that bundles the three analysis scripts used to produce the spectral, statistical, and Eckart\u2013Young figures in the report.
git clone https://github.com/NagusameCS/HyperTensor.git
cd HyperTensor/scripts/analysis
pip install -e .After installation the following commands are available on PATH:
| Command | Source script | Purpose |
|---|---|---|
| hypertensor-spectra | compute_spectra.py | SVD all attention + FFN matrices for layers 0/7/15/23/31; emits 3 PNGs and spectra_summary.json. |
| hypertensor-stats | statistical_tests.py | Paired t-test, Wilcoxon, bootstrap CI on rank_sweep_relative_to_baseline.csv. |
| hypertensor-eckart | eckart_young_bound.py | Eckart\u2013Young oracle vs GRC shared-basis comparison; layers 0/15/31; ranks 512\u20132048. |
Each script also remains runnable as a plain module: python compute_spectra.py, etc.
The scripts expect the GGUF model file path and the benchmark CSVs at the locations described in repro/QUICKSTART.md at the repo root. See the report's Reproduce section for the full recipe.
MIT. See repository root.
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