Developed by KageLabs, KageAI-7B-v1.2.5 is a high-performance bridge version in the KageAI series. This iteration focuses on absorbing the SUPER Dataset (10k Master Samples) before the final shift to Natural GaLore in v1.3.
This version uses QLoRA (Rank 64) with high gradient accumulation to stabilize the model's logic and refine its hardware-centric reasoning.
Training Method: High-Accumulation QLoRA (Rank 64 / Alpha 128)
Primary Focus: Deep System Architecture, Technical Reasoning, and Logical Consistency.
🧠 What's New in v1.2.5?
v1.2.5 serves as the "Intelligence Refiner." It builds upon the technical core of v1.2 with:
The SUPER Dataset Integration: Trained on a curated 10k Master Dataset designed to bridge the gap between pattern matching and actual reasoning.
Improved Hardware Logic: Better grasp of memory bandwidth, PCIe bottlenecks, and LLM server infrastructure.
Identity Patching: Significant reduction in identity drift; the model now firmly recognizes itself as KageAI by KageLabs.
Context Handling: Optimized for 2048 sequence length, providing more coherent long-form technical breakdowns.
🧪 Current Status & Road to v1.3
Vibe Check: The model has transitioned from a "Tech Guru" to a "Thought Partner."
Known Gaps: As an intermediate version, some complex "Natural Gradient" optimizations are reserved for the full v1.3 release on higher-end compute (Lightning AI).
Next Phase: v1.3 will utilize Natural GaLore to push this logic to GPT-4 level accuracy in coding and function calling.
🛠 Usage
This model uses the ChatML prompt format:
text
1<|im_start|>system
2You are KageAI by KageLabs, a High-End Technology and Hardware Specialist.<|im_end|>
3<|im_start|>user
4{query}<|im_end|>
5<|im_start|>assistant
6
Developed with ❤️ by KageLabs using Unsloth and the SUPER Dataset pipeline.
