0glm

0glm — Granular Brain

A small language model with all knowledge baked into a single 1.9 GB file. Load the artifact, ask questions — no retrieval, no external indexes, no corpus at inference time. Every sentence of an answer is traceable back to (document, position) in the source corpus.

GitHub: 0penAGI/0glm · Landing page: 0penagi.github.io/0glm

⚠️ Scope. This is not a general-purpose LLM. It was trained on a deliberately small research corpus (~16K documents: climate mechanics, astronomy, sleep science, Python docs, resume practice). Within that material it navigates coherently; outside it, it has nothing to navigate — the dataset you bring is the answers you get. The full bake pipeline ships here, so you can rebuild the artifact from your own texts.

Model facts

The parameter count is deliberately tiny: weights hold the navigation policy, the knowledge lives in the baked granule bank. That separation is what keeps every answer traceable.

Architecture

                      ┌────────────────────────── OFFLINE: BAKE ──────────────────────────┐
                      │                                                                    │
  corpus              │   granulation            semantics + style        teacher demos     │
┌──────────────┐      │  ┌──────────────┐      ┌──────────────────┐   ┌───────────────┐   │
│ raw web texts│─────▶│  │ µ micro      │      │ MiniLM-384 sems  │   │ ride planner  │   │
└──────────────┘      │  │ σ meso       │────▶ │ stylometry (32d) │   │ picks doc arc │   │
                      │  │ Ω macro      │      │ affect (V/A)     │   │ + corrections │   │
                      │  └──────────────┘      └────────┬─────────┘   └───────┬───────┘   │
                      │   syndication dedup             │                     │           │
                      │   canonization                  ▼                     ▼           │
                      │                       ┌──────────────────┐   ╔═══════════════════╗
                      │                       │ oscillatory      │   ║   DISTILLATION    ║
                      │                       │ field: clusters, ║──▶║ demo triples with ║
                      │                       │ transitions,     │   ║ correction moments│
                      │                       │ grain bank       │   ╚═══════════════════╝
                      │                       └────────┬─────────┘            │          │
                      └────────────────────────────────┼──────────────────────┼──────────┘
                                                       ▼                      ▼
                                            ╔══════════════════════════════════════╗
                                            ║             brain.pt  (1.9 GB)       ║
                                            ║  planner weights · granule bank ·    ║
                                            ║  doc embeddings · quality masks      ║
                                            ╚══════════════╦═══════════════════════╝
                                                           │
                      ┌────────────────── INFERENCE: NO RETRIEVAL ─────────────────────────┐
                      │                                                                    │
   "What causes       │        ┌───────────┐    qsem token                                │
    El Niño?" ────────┼───────▶│ question  │───────┐                                      │
                      │        │ embedding │       ▼                                      │
                      │        │  ┌─────────────────────────┐   predict next-grain        │
                      │        │  │ transformer over field  │───embedding ──┐             │
                      │        │  │ state (+ working memory)│               │ snap        │
                      │        │  └─────────────────────────┘               ▼             │
                      │        │                              ┌─────────────────────┐     │
                      │        │                              │ baked granule bank  │     │
                      │        │                              │ (nearest neighbor)  │     │
                      │        │                              └──────────┬──────────┘     │
                      │        │              repeat step ◀────────────────────┘              │
                      │        ▼                                                              │
                      │   answer = stitched verbatim granules, each traceable to (doc, pos)   │
                      └────────────────────────────────────────────────────────────────────┘

Quickstart

pip install -r requirements.txt

# ask the baked brain
python brain_chat.py --brain brain.pt --ask "What causes El Nino?"

# interactive session
python brain_chat.py --brain brain.pt --chat

Rebuild the artifact from your own corpus

python granulate.py          # corpus → granules → semantics → field caches
python gen_demos.py          # teacher demonstrations (correction moments)
python train_brain.py        # distill teacher into the planner
python bake_brain.py         # pack everything into one brain.pt

Files

The audio modality (sonification of trajectories, 0MGE heritage) lives in the GitHub repo and is not part of this artifact yet.

License

MIT.