RealPirate786/Minesweeper_agent_Qwen3_0.6B-SFT-Thinking
TEXT GENERATIONConcurrent Unit Cost:1Model Size:0.8BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 9, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The RealPirate786/Minesweeper_agent_Qwen3_0.6B-SFT-Thinking is a 0.8 billion parameter Qwen3 model, developed by RealPirate786. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is specifically designed for tasks related to Minesweeper agent behavior, leveraging its efficient training for specialized applications.
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Model Overview
This model, developed by RealPirate786, is a fine-tuned version of the Qwen3 architecture, specifically the unsloth/qwen3-0.6b-unsloth-bnb-4bit base model. It features approximately 0.8 billion parameters and was trained with a context length of 32768 tokens.
Key Characteristics
- Efficient Training: The model was fine-tuned using Unsloth and Huggingface's TRL library, which allowed for a 2x faster training process compared to standard methods.
- Specialized Application: This particular iteration is designed as a "Minesweeper agent," indicating its intended use for tasks or simulations related to the game Minesweeper.
- License: The model is released under the Apache-2.0 license.
Potential Use Cases
- Minesweeper AI Development: Ideal for researchers and developers working on AI agents for the game Minesweeper.
- Efficient Fine-tuning Demonstrations: Can serve as an example of how to leverage Unsloth for accelerated model training on specific tasks.
- Small-Scale Specialized LLM Applications: Suitable for scenarios requiring a compact yet specialized language model for focused tasks.