SHADOW 50M Instruct v1.1.2, kernel fix

Kernel fix, container unchanged. The trail in the memory index no longer lets a warmed link outrank a better word match, and rival links decay on every confirmed copy. Found by CarefulHamster7184 on r/MachineLearning; the ablation with before and after numbers is in benchmarks/trail_ablation/. The Windows kernel is now a static build with no DLL dependencies. Every published answer is unchanged: 30 of 30 one-shot prompts and 37 of 37 samples token-identical, GOLDEN 8 of 8 on Windows, Linux and the browser build.

The model file is the same as v1.1 (19,799,680 bytes).

SHADOW 50M Instruct v1.1

Version 1.1: the same weights as 1.0 with 8,600 English word pieces added to the frozen vocabulary table, so lowercase names and places arrive whole. Nothing was trained; every published answer is unchanged, GOLDEN 8/8. The container carries the archive blobs (identifier flags, case-fold map, stop list) extended to the new rows, so memory on disk works as before. 19.8 MB. Measurements in reports/EXTENSION_2026-09-13.md. Use this one.

SHADOW 50M Instruct v1.0.0

The 19 MB deployment container: ternary weights, the frozen 512-bit vocabulary table, runtime constants and the self-test prompt. Golden parity 8/8 through both prebuilt kernels.

Download shadow50_instruct.shdw and drop it into deployment/, or clone the repository, which already contains it.

python shadow_chat.py

Runs offline on a CPU at roughly 1,700-2,300 tokens per second in about 39 MB of RAM. Measurements and the prompts behind them are in README.md, SAMPLES.md and RECEIPTS.md.