Spaces:
Running
Running
metadata
title: README
emoji: 🔩
colorFrom: gray
colorTo: blue
sdk: static
pinned: false
thumbnail: >-
https://cdn-uploads.huggingface.co/production/uploads/69c6fa91d74254bbb63f3348/10R3gfJB36vsT0scshb5e.png
Tinman Lab
Autonomous Machines. Second-Order Systems.
AGENT MEMORY · ADVERSARIAL SAFETY · AGENTIC ECONOMY · PERCEPTION SYSTEMS · APPLIED RESEARCH
We build on-device AI systems that reason, remember, and self-correct — small models designed to run autonomously at the edge with calibrated uncertainty and adversarial robustness.
Research Areas
- Agent Memory — Encrypted semantic memory infrastructure for persistent agent context
- Adversarial Safety — Multi-agent stress-testing and trust verification for autonomous systems
- Perception Systems — On-device vision, voice, and multimodal understanding
- Disposition Distillation — A three-arc study finding that imitation, attention-head tempering, and frozen-base sidecars all fail to move judge-measured disposition without damaging content quality at sub-billion scale (arXiv:2604.11867).
Open-Source Releases
Tinman SmolOmni (MLA) — small omnimodal models with multi-head latent attention.
| Model | Description |
|---|---|
| Tinman-SmolOmni-MLA-256M | 256M parameter omnimodal |
| Tinman-SmolOmni-MLA-500M | 500M parameter omnimodal |
| Tinman-SmolOmni-MLA-Toolkit | Training and inference toolkit |
Tinman Companion — Gemma 4 fine-tunes for on-device companion use cases.
| Model | Description |
|---|---|
| Tinman-gemma4-companion-merged | Full-precision merged model |
| Tinman-gemma4-companion-gguf | GGUF quantized for llama.cpp |
| Tinman-gemma4-companion-litert-lm | LiteRT-LM for on-device deployment |
| Tinman-gemma4-companion-sft | SFT checkpoint |
| Tinman-gemma4-companion-dpo | DPO checkpoint |