Update README.md

README.md

@@ -39,7 +39,7 @@ curriculum-informed reinforcement learning framework to enhance logical correctn
 ## Model Details
 
 CURE-MED-14B is part of the CURE-MED family of models, designed to address the challenges of multilingual medical reasoning in large language models (LLMs).
-Built on the Qwen2.5-14B base model, it incorporates a curriculum-informed reinforcement learning approach that integrates code-switching-aware supervised fine-tuning (SFT)
+Built on the Qwen/Qwen2.5-14B-Instruct model, it incorporates a curriculum-informed reinforcement learning approach that integrates code-switching-aware supervised fine-tuning (SFT)
 and Group Relative Policy Optimization (GRPO) to improve performance on open-ended medical queries across 13 languages, including underrepresented ones such as Amharic, Yoruba, and Swahili.
 The model is trained and evaluated using CUREMED-BENCH, a high-quality multilingual open-ended medical reasoning benchmark with single verifiable answers.