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README.md

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 This repository contains the **LoRA checkpoint** for **SPORT**, a framework that enables multimodal agents to improve iteratively through self-generated tasks and preference-based optimization.
-We finetuned **Qwen2-VL-7B** using **LoRA adapters** and **Direct Preference Optimization (DPO)**, making the model more effective at reasoning about multimodal tasks and aligning with preference signals.
+We finetuned **Qwen2-VL-7B-Instruct** using **LoRA adapters** and **Direct Preference Optimization (DPO)**, making the model more effective at reasoning about multimodal tasks and aligning with preference signals.
 
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 ## 📋 Key Features
 
-* **LoRA Fine-tuning**: Lightweight finetuning on top of Qwen2-VL-7B for efficient adaptation.
+* **LoRA Fine-tuning**: Lightweight finetuning on top of Qwen2-VL-7B-Instruct for efficient adaptation.
 * **DPO Training**: Preference-based optimization for stronger alignment without human annotations.
 * **Task Synthesis**: Multimodal task generation via LLMs for broad coverage.
 * **Step Exploration**: Multiple candidate actions sampled per decision point.