Ilia2003Mah/qwen2.5-1.5b-gsm8k-train-step7500
TEXT GENERATIONConcurrency Cost:1Model Size:1.5BQuant:BF16Ctx Length:32kPublished:Mar 24, 2026Architecture:Transformer Warm
Ilia2003Mah/qwen2.5-1.5b-gsm8k-train-step7500 is a 1.5 billion parameter language model based on the Qwen2.5 architecture. This model has been fine-tuned specifically for mathematical reasoning tasks, particularly on the GSM8K dataset. Its primary strength lies in solving grade school level math problems, making it suitable for applications requiring numerical problem-solving capabilities.
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Model Overview
Ilia2003Mah/qwen2.5-1.5b-gsm8k-train-step7500 is a 1.5 billion parameter language model built upon the Qwen2.5 architecture. This model has undergone specific fine-tuning, with its training extending to step 7500, primarily targeting the GSM8K dataset. The focus of this training is to enhance its performance in mathematical reasoning.
Key Capabilities
- Mathematical Reasoning: Optimized for solving grade school level mathematical word problems, as indicated by its fine-tuning on the GSM8K dataset.
- Qwen2.5 Architecture: Leverages the foundational capabilities of the Qwen2.5 model family.
- Compact Size: With 1.5 billion parameters, it offers a relatively efficient footprint for deployment compared to larger models.
Good For
- Educational Tools: Developing applications that assist students with math homework or provide step-by-step solutions.
- Automated Problem Solving: Integrating into systems that require automated solutions for arithmetic and basic algebraic problems.
- Research in Mathematical LLMs: As a base for further experimentation and fine-tuning on specific mathematical domains.