xw1234gan/SMOKE_Merging_Prob_Qwen2.5-7B-Instruct_MATH_lr1e-05_mb2_ga4_n16_seed42
The xw1234gan/SMOKE_Merging_Prob_Qwen2.5-7B-Instruct_MATH_lr1e-05_mb2_ga4_n16_seed42 model is a 7.6 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. This model is specifically fine-tuned for mathematical reasoning tasks, distinguishing it from general-purpose LLMs. With a context length of 32768 tokens, it is designed to excel in complex problem-solving and numerical applications.
Loading preview...
Model Overview
The xw1234gan/SMOKE_Merging_Prob_Qwen2.5-7B-Instruct_MATH_lr1e-05_mb2_ga4_n16_seed42 is a 7.6 billion parameter instruction-tuned model built upon the Qwen2.5 architecture. This model is distinguished by its specific fine-tuning for mathematical reasoning and problem-solving, making it a specialized tool for numerical and logical tasks.
Key Capabilities
- Specialized Mathematical Reasoning: Optimized to handle complex mathematical problems and queries.
- Instruction Following: Designed to accurately follow instructions for task execution.
- Large Context Window: Supports a context length of 32768 tokens, enabling processing of extensive problem descriptions or multi-step calculations.
Good For
- Mathematical Applications: Ideal for tasks requiring strong numerical and logical deduction.
- Academic Research: Useful for researchers working on AI in mathematics or quantitative fields.
- Problem Solving: Suited for scenarios where precise, step-by-step mathematical solutions are required.