# Dev-AI: Fine-Tuned 27B Code Review Model
**Goal:** Train a 27B model on software development data, run it on CPU as a code review partner.
## Architecture
```
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ Dataset │───▶│ QLoRA Train │───▶│ Merge + │
│ (Code, SO, │ │ (CPU, 4-bit)│ │ llama.cpp │
│ Docs, PRs) │ │ ~14 days │ │ Server │
└──────────────┘ └──────────────┘ └──────────────┘
│
▼
┌──────────────┐
│ Code Review │
│ API (port │
│ 8081) │
└──────────────┘
```
## Workflow
1. Vincent writes code → 2. POST to fine-tuned model → 3. Model reviews/corrects → 4. Vincent iterates
## Hardware
- **Training:** Ryzen 9 9900X CPU, 60GB RAM (no GPU)
- **Inference:** llama.cpp server, ~17GB RAM for Q4 27B model
- **GPU (4090):** Reserved for Vincent's own inference, not touched
## Status
- [ ] Dataset collection
- [ ] Training script with checkpoint resumption
- [ ] systemd background service
- [ ] Model merge + GGUF conversion
- [ ] llama.cpp server setup
- [ ] Code review integration workflow