hector-gr/RLCR-v4-ks-uniqueness-cold-math
TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Mar 16, 2026Architecture:Transformer Warm
hector-gr/RLCR-v4-ks-uniqueness-cold-math is a 7.6 billion parameter language model fine-tuned from Qwen/Qwen2.5-7B. Developed by hector-gr, this model was trained using the TRL library and incorporates the GRPO method, which is designed to enhance mathematical reasoning capabilities. It is optimized for tasks requiring advanced logical and mathematical problem-solving, building upon the robust foundation of the Qwen2.5 architecture.
Loading preview...
Model Overview
This model, hector-gr/RLCR-v4-ks-uniqueness-cold-math, is a 7.6 billion parameter language model. It is a fine-tuned variant of the Qwen/Qwen2.5-7B base model, developed by hector-gr.
Key Capabilities
- Enhanced Mathematical Reasoning: The model was trained using the GRPO method, as introduced in the DeepSeekMath paper, specifically to improve its performance on mathematical reasoning tasks.
- TRL Framework: Fine-tuned with the TRL library, indicating a focus on reinforcement learning from human feedback or similar training paradigms.
- Robust Base: Leverages the strong foundational capabilities of the Qwen2.5-7B architecture.
Good For
- Applications requiring advanced mathematical problem-solving.
- Tasks that benefit from logical reasoning and structured thought processes.
- Developers looking for a model with a specialized focus on quantitative analysis and complex calculations.