jetbabareal/gemma-3-1b-elite

Model Overview

The jetbabareal/gemma-3-1b-elite model is an experimental variant of the Gemma architecture, developed by jetbabareal. It introduces a novel technique called "Elite Neuron Fusion" to enhance reasoning and logic capabilities in smaller language models (1-2 billion parameters).

Key Capabilities & Methodology

Unlike conventional model merging techniques, Elite Neuron Fusion employs a surgical, density-based injection algorithm:

• Targeted Injection: Identifies specific "resonance pairs" between source (early-mid) and target (mid-deep) layers of the Gemma architecture.
• Delta Vector Calculation: Computes the difference (delta vector) between these identified layers.
• Density Selection: Selects only the top 20% of neurons exhibiting the highest activation or change.
• Scaled Injection: These "elite" neurons are then injected into the target layers using a specific alpha scaling factor (0.40), modifying only a small fraction of the weights per layer.

This method aims to improve logical processing without disrupting the model's existing knowledge base or introducing severe hallucinations.

Technical Configuration Highlights

• Source Layers: 12-16
• Target Layers: 17-21
• Density: 0.20 (20% of weights modified per layer)
• Alpha: 0.40

Intended Use

This model is an experimental exploration into enhancing the reasoning and logic of compact language models, making it suitable for research and development focused on improving the cognitive abilities of smaller LLMs.