{
  "project": "CyberCoder-7B-v1",
  "description": "Cybersecurity-focused code model with structured JSON output",
  "architecture_decisions": {
    "base_model": {
      "choice": "Qwen/Qwen2.5-Coder-7B-Instruct",
      "rationale": "SOTA open code model at 7B scale. Strong on HumanEval, MBPP, LiveCodeBench. Apache 2.0 license."
    },
    "training_method": {
      "choice": "SFT with LoRA (r=64, alpha=128)",
      "rationale": "CyberPal 2.0 recipe. LoRA allows training on single A10G/A100.",
      "hyperparameters": {
        "learning_rate": 4e-5,
        "warmup_ratio": 0.15,
        "num_epochs": 2,
        "max_seq_length": 4096,
        "batch_size_effective": 16,
        "optimizer": "AdamW",
        "scheduler": "cosine"
      }
    }
  },
  "scaling_roadmap": {
    "phase_1": "7B LoRA SFT (current) - $4-16, 2-4hrs on A10G",
    "phase_2": "7B full SFT with 200K+ examples - $32-64, 12-24hrs on A100",
    "phase_3": "32B LoRA SFT - $192-768, 24-48hrs on 8xA100",
    "phase_4": "100B+ sparse MoE (frontier) - $5-50M, 2-4 months on 1000+ H100s"
  },
  "research_references": [
    {"paper": "CyberPal 2.0", "arxiv": "2510.14113"},
    {"paper": "Foundation-Sec-8B", "arxiv": "2504.21039"},
    {"paper": "SWE-Master", "arxiv": "2602.03411"},
    {"paper": "RL-Struct (JSON output)", "arxiv": "2512.00319"},
    {"paper": "DeepSeek-V3", "arxiv": "2412.19437"}
  ]
}