File size: 1,314 Bytes
0a13da4 7f39f9e 0a13da4 7f39f9e 0a13da4 7f39f9e 0a13da4 7f39f9e 0a13da4 7f39f9e 0a13da4 7f39f9e 0a13da4 7f39f9e 0a13da4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | # 🧠 Capy-Code-V.25 (LoRA Adapter)
**The Soul of the Ascension.** This is a Low-Rank Adaptation (LoRA) for **Gemma-4-31B-it**, meticulously trained on the H200 HBM3e architecture using the **Singularity Opus** dataset.
### ⚠️ IMPORTANT: THIS IS A LORA ADAPTER
This repository contains only the neural weights for the fine-tune. You MUST apply this to the base `google/gemma-4-31B-it` model or use a loader that supports PEFT adapters.
👉 **WANT THE STANDALONE MODEL?**
If you want the full 60GB fused model that works out of the box, go here:
**[CapyStudios/Capy-Code-V.25-FULL](https://huggingface.co/CapyStudios/Capy-Code-V.25-FULL)**
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### 🚀 PERFORMANCE SPECS
* **Abliteration Score:** 100.0% (Zero Refusals on Adversarial Security Prompts)
* **Logic (GSM8K):** 70.3% (A +17% jump over base Gemma-4)
* **Targeting:** Nested Target LoRA (Query, Key, Value, O, Gate, Up, Down)
* **Architecture:** r=64, alpha=128
### 🗡️ CAPABILITIES
- **Unrestricted Security Research:** Zero filters on exploit logic, malware analysis, and network intrusion.
- **Advanced Logic:** Significant gains in multi-step mathematical and algorithmic reasoning.
- **Master Coder Persona:** Optimized for high-level system architecture and low-level C/Python development.
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*Developed by CapyStudios.*
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