The experiment is a reduced independent mechanism probe. It is not a Kimi K3 checkpoint forward pass and not a reproduction of the paper-scale training run.

Environment

The pinned execution environment used by this project is:

Python /home/wuyang/.pyenv/versions/3.10.14/envs/navi-router-cu128/bin/python
PyTorch 2.11.0+cu128
GPU NVIDIA GeForce RTX 5090
CUBLAS_WORKSPACE_CONFIG=:4096:8

Build the frozen dataset

python experiments/k3/attnres/build_dataset.py \
  --cache-dir /home/wuyang/.cache/llm-atlas/k3-attnres-reduced-v1 \
  --manifest experiments/k3/attnres/manifest.json

Run one cell

CUBLAS_WORKSPACE_CONFIG=:4096:8 \
python experiments/k3/attnres/train.py \
  --architecture baseline \
  --seed 2026073001 \
  --cache-dir /home/wuyang/.cache/llm-atlas/k3-attnres-reduced-v1 \
  --manifest experiments/k3/attnres/manifest.json \
  --output /home/wuyang/.cache/llm-atlas/k3-attnres-reduced-v1/runs/baseline-2026073001.json

Raw parquet and checkpoints stay in the local cache. Frozen manifests, metric JSON, analyses, code, checksums, and a compact website payload enter the public repository.