Yunseo27/gemma-3-1b-it-Math-SFT-Math-SFT
Yunseo27/gemma-3-1b-it-Math-SFT-Math-SFT is a 1 billion parameter instruction-tuned language model based on the Gemma architecture, developed by Yunseo27. This model is specifically fine-tuned for mathematical tasks and reasoning, leveraging Supervised Fine-Tuning (SFT) on mathematical datasets. With a context length of 32768 tokens, it is designed to excel in complex mathematical problem-solving and related applications.
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Overview
This model, Yunseo27/gemma-3-1b-it-Math-SFT-Math-SFT, is a 1 billion parameter instruction-tuned language model built upon the Gemma architecture. It has undergone Supervised Fine-Tuning (SFT) with a specific focus on mathematical tasks, aiming to enhance its capabilities in numerical reasoning and problem-solving. The model supports a substantial context length of 32768 tokens, allowing it to process and understand longer mathematical problems and related instructions.
Key Capabilities
- Mathematical Reasoning: Optimized for understanding and solving mathematical problems.
- Instruction Following: Designed to accurately follow instructions, particularly in a mathematical context.
- Extended Context: Benefits from a 32768-token context window, useful for multi-step problems or complex mathematical descriptions.
Good for
- Applications requiring mathematical problem-solving.
- Educational tools for math assistance.
- Research into mathematical reasoning in LLMs.
- Tasks where precise instruction following in a numerical domain is critical.