GoldenGrapeGentleman1/battle-game-agent-full-sft
GoldenGrapeGentleman1/battle-game-agent-full-sft is a 4 billion parameter Qwen3-4B model fine-tuned by GoldenGrapeGentleman1. It is specifically designed to act as an agent for turn-based battle games, processing raw battle protocol lines to output strategic moves. This model excels as a competitive tier agent for games like gen9randombattle, capable of direct inference or serving as a base for battle-oriented GRPO.
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Model Overview
GoldenGrapeGentleman1/battle-game-agent-full-sft is a specialized 4 billion parameter language model, built upon the Qwen3-4B architecture. It has been extensively fine-tuned on approximately 2.3 million turn-based battle game replay logs, enabling it to understand and respond to raw battle protocol lines.
Key Capabilities
- Game Agent Functionality: Processes battle protocol lines to generate appropriate game actions, such as
move …orswitch …. - Specialized Training: Leverages a large dataset of real game replay logs for highly specific domain expertise.
- Competitive Performance: Designed to operate as a competitive tier agent, particularly noted for gen9randombattle.
Training Details
The model underwent Full SFT (Supervised Fine-Tuning) with merged weights. Training was conducted on AMD Instinct MI300X hardware, utilizing ROCm and bfloat16 precision. The base model is Qwen/Qwen3-4B.
Use Cases
- Direct Inference: Can be loaded and used immediately for generating game actions in turn-based battle scenarios.
- Base for GRPO: Serves as a strong foundation for further reinforcement learning methods like GRPO (Generalized Policy Optimization) in battle-oriented AI development.