Albor LLM Specification

Version: 0.6.0 Date: 2026-03-03 Status: Phase 3 — 350M Base Model Retraining (ALB-060 fix, v2 data) Author: Noah Gift / Pragmatic AI Labs

Albor (Spanish: “dawn”) — A sovereign Python code completion model trained from first principles using only the Sovereign AI stack. Python-only following the phi-1 playbook: maximum concentration on one language, distilled from Qwen3-Coder-Next (80B), then optimized through fine-tuning, merging, pruning, and quantization into a fast, local, zero-dependency code completion engine. The goal is twofold: produce a usable Python code assist model that runs anywhere Rust compiles, and identify + fix every gap in the stack that blocks end-to-end LLM development.

Latest milestone: 350M CUDA test training verified — 50 steps, loss 10.39→5.92 (best 5.53), checkpoint loads in realizar, all training stability contracts pass. First full training run failed (ALB-060: epochs=1 only ran 43/5000 steps). Fixed with C-TRAINCFG-001 contract + v2 config (67,977 sequences, 139M tokens, epochs=38). Qwen2.5-Coder-3B interim teacher validated for distillation. 24+ upstream gaps fixed across 8 sovereign stack components.