pepper-desk-e2b — the MNN singularity desk, distilled

A 2B-class specialist that reads a wire of headlines and writes a grounded broadcast report — sources attributed, rumors adjudicated, unknowns said out loud. It is the research-desk brain of Pepper, the open-source on-device news anchor (pepper.software · github.com/bunnycompany/pepper · watch her: pepper.watch).

MoltBench (12 bundles, 12 blind judges, deterministic rotation)

Model	Blind wins	Grounding	Adjudication	Persona
pepper-desk-e2b (this, 2B)	11/12	88.6%	4.67/5	3.75/5
Qwen2.5-7B-Instruct-4bit	1/12	77.5%	2.67	1.42
pepper-7b (persona LoRA)	0/12	50.0%	2.00	1.83

Benchmark, bundles, scorer, and protocol: bench/ in the repo. The origin story matters: the first Pepper model failed this benchmark against its own base (38.1% vs 64.5% grounding) — that failure became the release gate this model had to clear.

Format: think, then speak

Trained think-then-speak. Given wire notes, she emits DESK NOTES: (a private source-weighing analysis) then ON AIR: (the broadcast). Consumers show or strip the notes; score only the broadcast.

System prompt and wire format: see bench/README.md and the repo's gen_eval_v2 harness. Use max_tokens ≥ 500 — tighter caps truncate her sign-offs (it cost her one judged bundle).

Training

• Base: google/gemma-4-e2b-it via mlx-community/gemma-4-e2b-it-4bit
• LoRA (mlx-lm 0.31, git), lr 4e-5, batch 4, seq 1800, grad-checkpoint, iteration-200 checkpoint selected by validation loss (1.557; later checkpoints overfit — the full curve is documented in the repo)
• Data: 452 examples — 412 claim-verified wire→report pairs authored against the live August-2026 news cycle with explicit DESK NOTES reasoning (including deliberately contaminated bundles with exemplar adjudications), her 65 real broadcast segments, and a 40-riff persona sprinkle
• Trained on an M3 Ultra in ~90 minutes; reproducible on consumer Apple Silicon

Limitations

She is grounded, not omniscient: judges recorded occasional invented connective detail, "peer-reviewed" applied to preprints, and style drift on very thin wires. She is built to work FROM provided wire notes — as a freestanding chatbot she is out of her element and says so less often than she should. English-first. Not for advice of any kind.

License & lineage

Weights are a derivative of Gemma and ship under the Gemma Terms of Use. The surrounding desk (app, bench, pipeline) is AGPL-3.0. Lineage: Danger Ghost (VTuber era) → MNN research anchor → this desk brain.

MNN — all your models, all the time. 🌶