README.md

---
title: Construction Code-Citation Model
emoji: 🏗️
colorFrom: blue
colorTo: yellow
sdk: gradio
sdk_version: 4.44.1
python_version: "3.12"
app_file: app.py
pinned: false
license: mit
short_description: Llama 4 Scout 17B MoE for OSHA hazard + citation
---

# Construction Code-Citation Model (v3 · Llama 4 Scout · AutoScientist)

Llama 4 Scout 17B-16E MoE fine-tuned by **AutoScientist** for construction-safety incident classification and OSHA 29 CFR 1926 citation grounding. **82% win rate** on our task vs base Llama 4 Scout, and **72% win rate on the broader Governance benchmark** — no specialization trade-off.

Inference goes through Together AI's hosted endpoint. v2 (Llama 3.2 3B) auto-falls-back if the Together endpoint is unavailable, so the demo cannot go dark.

- **v3 (primary):** [rigidhat/llama-4-scout-17b-construction-codecite-v3](https://huggingface.co/rigidhat/llama-4-scout-17b-construction-codecite-v3) — 82% task, 72% Governance
- **v2 (fallback):** [rigidhat/llama-3.2-3b-construction-codecite-v2](https://huggingface.co/rigidhat/llama-3.2-3b-construction-codecite-v2) — 77% task
- **Dataset:** [rigidhat/construction-code-corpus-v1](https://huggingface.co/datasets/rigidhat/construction-code-corpus-v1)
- **Baseline (Qwen 2.5 1.5B QLoRA):** [rigidhat/qwen-2.5-construction-codecite-v1](https://huggingface.co/rigidhat/qwen-2.5-construction-codecite-v1)

Built for the [Adaption Labs AutoScientist Challenge](https://adaptionlabs.ai/auto-scientist), **"All Other Domains"** category. Credit to **Adaptive Data by Adaption**.