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license: mit
base_model: google/gemma-4-26B-A4B-it
tags:
- lora
- gemma4
- moe
- peft
- encinitas
- cybersecurity
- virgil
library_name: peft
pipeline_tag: text-generation
---
# encinitas-gemma4-lora
LoRA adapter for **encinitas** — a VIRGIL-style blue-team fine-tune on [Gemma 4 26B A4B](https://huggingface.co/google/gemma-4-26B-A4B-it).
Trained for endpoint security investigation: MITRE ATT&CK mapping, Sigma rule analysis, malware behavior reasoning, and structured defender recommendations in the `<reasoning>...</reasoning><answer>{JSON}</answer>` contract.
Uses Fireworks `fused_peft_3d_v1` MoE expert layout. **Stock PEFT cannot load this adapter alone** — use the VIRGIL inference scripts that merge fused expert LoRA:
https://github.com/artk-code/virgil/tree/main/inference/encinitas
## Quick start
```bash
git clone https://github.com/artk-code/virgil.git
cd virgil/inference/encinitas
cp encinitas.env.example encinitas.env # add HF_TOKEN locally — never commit
# Accept Gemma 4 license: https://huggingface.co/google/gemma-4-26B-A4B-it
bash fix_encinitas_gfx1151_torch.sh # AMD Strix Halo / gfx1151
# bash setup_cuda_venv.sh # NVIDIA 48GB+
./run_encinitas_local.sh "Your prompt"
```
## Requirements
- Base model: `google/gemma-4-26B-A4B-it` (~49 GB, gated)
- 48 GiB+ VRAM (fp16); Strix Halo (~96 GiB unified) tested on ROCm
- Hugging Face token with Gemma 4 license accepted
## Evaluation (summary)
Public OOD cyber eval (Meta CyberSecEval-inspired prompts). Full methodology:
https://www.artkaiser.net/blog/encinitas-cheaper-better-cyber-inference
| Model | TTP % | Actionable % | Format (0-4 avg) |
|-------|-------|--------------|------------------|
| Encinitas LoRA | 100% | 50% | 2.0 |
| Gemma4-26b-a4b-it (base) | 100% | 67% | 3.0 |
| Kimi k2p7-code | 100% | 100% | 1.3 |
encinitas excels at **concise, parseable, contract-aligned** outputs for SOC and agent workflows.
Training context (VIRGIL corpus): https://www.artkaiser.net/blog/custom-cybersecurity-models-fireworks
## License
- Scripts in [artk-code/virgil](https://github.com/artk-code/virgil): MIT
- Adapter weights: MIT
- Base Gemma 4: Google Gemma license (accept on Hugging Face)
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