# Stage 1 state Task: `docs/stage1-training-task.md`. Settings and weights: `train/README.md`. Updated 2026-10-03 18:35. ## Done - Step 0 (setup): `train/.venv` (Python 3.11.17, uv), `mlx-lm` 0.32.0 / `mlx` 0.32.3. Model `mlx-community/Qwen3.8-27B-4bit` at `~/models/Qwen3.8-27B-4bit` (affine 4 bit, group 64, 16.1 GB; base `Qwen/Qwen3.8-27B`). The Ollama NVFP4 weights do not load in mlx_lm (global scale). - Server: `train/serve.sh` (`mlx_lm.server`, port 8080, thinking on with `reasoning_effort` medium, temperature 0.2, top_p 0.95, top_k 20, min_p 0, max tokens 32768). Tool-call test passed. - Eval subset (Kral decision): `train/subset.json` (copy `runs/stage1/subset.json`), 25 tasks. The task document says "all accepted tasks" for step 2; Kral changed it to this subset. Use the same list after training. - Runner: `train/baseline.py --label