RealPirate786/Minesweeper_agent_Qwen3_4B-SFT-Thinking
RealPirate786/Minesweeper_agent_Qwen3_4B-SFT-Thinking is a 4 billion parameter Qwen3 model developed by RealPirate786. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for specific applications, likely related to agentic behavior or game environments such as Minesweeper, leveraging its Qwen3 architecture for task-specific performance.
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Model Overview
RealPirate786/Minesweeper_agent_Qwen3_4B-SFT-Thinking is a 4 billion parameter Qwen3 model, developed by RealPirate786. It was fine-tuned from unsloth/qwen3-4b-unsloth-bnb-4bit using the Unsloth library and Huggingface's TRL library. This approach facilitated a 2x faster training process compared to standard methods.
Key Characteristics
- Base Model: Qwen3 architecture.
- Parameter Count: 4 billion parameters.
- Training Efficiency: Utilizes Unsloth for accelerated fine-tuning.
- License: Released under the Apache-2.0 license.
Potential Use Cases
This model is likely specialized for tasks requiring agentic capabilities, particularly within game environments or simulations. Its fine-tuning suggests an optimization for specific decision-making or strategic tasks, potentially in contexts like playing Minesweeper or similar rule-based games. Developers looking for a compact, efficiently trained Qwen3 model for agent-based applications could find this model suitable.