KhaledAalnobani/Qwen2.5-Math-1.5B
TEXT GENERATIONPricing:Input $0.04 / Cached $0.008 / Output $0.08Concurrent Unit Cost:1Model Size:1.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 5, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
KhaledAalnobani/Qwen2.5-Math-1.5B is a 1.5 billion parameter Qwen2.5 model developed by KhaledAalnobani, fine-tuned for mathematical tasks. It was trained using Unsloth and Huggingface's TRL library, offering a 32768 token context length. This model is optimized for efficient processing and performance in mathematical reasoning and problem-solving applications.
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Model Overview
KhaledAalnobani/Qwen2.5-Math-1.5B is a 1.5 billion parameter language model, developed by KhaledAalnobani, specifically fine-tuned for mathematical applications. It is based on the Qwen2.5 architecture and leverages a 32768 token context window, making it suitable for handling complex mathematical problems and extended reasoning chains.
Key Capabilities
- Mathematical Proficiency: This model is specialized for mathematical tasks, indicating enhanced performance in areas requiring numerical reasoning, equation solving, and quantitative analysis.
- Efficient Training: The model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process. This suggests an optimized and efficient development approach.
- Qwen2.5 Architecture: Built upon the Qwen2.5 foundation, it benefits from the advancements and capabilities inherent in this model family.
Good For
- Mathematical Problem Solving: Ideal for applications requiring accurate and efficient solutions to mathematical challenges.
- Research and Development: Suitable for researchers and developers working on projects that demand strong mathematical reasoning from an LLM.
- Educational Tools: Can be integrated into tools designed to assist with learning or solving mathematical problems.