KM1803/Minesweeper_agent_Qwen3_0_6B_2507
KM1803/Minesweeper_agent_Qwen3_0_6B_2507 is a 0.8 billion parameter Qwen3 model developed by KM1803, fine-tuned from unsloth/qwen3-0.6b-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for specific agentic tasks, likely related to Minesweeper, leveraging its compact size and efficient training for focused applications.
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Overview
KM1803/Minesweeper_agent_Qwen3_0_6B_2507 is a compact 0.8 billion parameter language model, developed by KM1803. It is fine-tuned from the unsloth/qwen3-0.6b-unsloth-bnb-4bit base model, indicating a focus on efficiency and specialized performance. The model was trained with the assistance of Unsloth and Huggingface's TRL library, which enabled a 2x faster training process.
Key Characteristics
- Base Model: Qwen3 architecture.
- Parameter Count: 0.8 billion parameters, making it suitable for resource-constrained environments or specific, focused tasks.
- Training Efficiency: Leverages Unsloth for significantly faster fine-tuning.
- Context Length: Supports a context length of 32768 tokens.
- License: Distributed under the Apache-2.0 license.
Use Cases
This model is specifically named "Minesweeper_agent," suggesting its primary application is as an agent for tasks related to the game Minesweeper. Its compact size and efficient training make it ideal for:
- Developing intelligent agents for game environments.
- Applications requiring fast inference and low computational overhead.
- Specialized tasks where a smaller, highly focused model is more effective than a general-purpose large language model.