Shepherd-Alpha by Convergent Intelligence LLC is a 2 billion parameter tactical reasoning model based on Qwen3-1.7B, fine-tuned with a novel BiCell Depth Dispersal methodology. It specializes in generating structured dual-perspective military scenario analysis, providing both adversary attack reasoning and defensive countermeasures. This model is optimized for defense AI applications requiring anticipatory tactical analysis.
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Shepherd-Alpha: Tactical AI Reasoning Model
Shepherd-Alpha is the first public model in the Shepherd program by Convergent Intelligence LLC, designed for defense AI applications. This 2 billion parameter model, built on Qwen3-1.7B, excels at generating structured dual-perspective analysis for military scenarios.
Key Capabilities
- Dual-Perspective Reasoning: Provides both "attack reasoning" (how an adversary would exploit a situation) and "defense reasoning" (how to counter and mitigate threats).
- BiCell Depth Dispersal: Utilizes a novel training methodology that asymmetrically trains transformer layers, separating representation encoding from task-specific reasoning to force genuine specialization.
- Tactical Scenario Analysis: Trained on 150 dual-perspective tactical scenarios from the ZennyKenny/tactical-military-reasoning-v.1.0 dataset.
Good For
- Analyzing military or security-related tactical scenarios.
- Developing AI systems for autonomous defense applications.
- Research into specialized reasoning models and novel training methodologies.
Limitations
As an alpha release, it has a small training set, which limits tactical depth. The base model's <think> generation pattern may sometimes override structured output, requiring specific generation configurations.