Update README.md

README.md

@@ -1,7 +1,7 @@
 ---
 license: mit
 library_name: gguf
-base_model: Qwen/Qwen2.5-Math-7B
+base_model: Qwen/Qwen2.5-Coder-7B
 datasets:
 - AI-MO/NuminaMath-TIR
 tags:
@@ -21,21 +21,21 @@ tags:
 
 # ΣMath — Visual Computation Engine v2.0
 
-### **Powered by Qwen-Math & NuminaMath-TIR**
+### **Powered by Qwen2.5-Coder-7B & NuminaMath-TIR**
 
 **Developed by: Khurram Pervez, Assistant Professor of Mathematics**
 
-**ΣMath Core** is a high-performance mathematical visualization engine that bridges the gap between deep symbolic reasoning and real-time interactive rendering. By leveraging the **NuminaMath-TIR** dataset, the model excels at **Chain-of-Thought (CoT)** reasoning, allowing it to solve complex geometric problems before translating them into interactive code.
+**ΣMath Core** is a high-performance mathematical visualization engine that bridges the gap between deep symbolic reasoning and real-time interactive rendering. By leveraging a fine-tuned **Qwen2.5-Coder-7B** backbone with the **NuminaMath-TIR** dataset, the model excels at **Chain-of-Thought (CoT)** reasoning, allowing it to solve complex geometric problems before translating them into interactive code.
 
 The engine utilizes a specialized **Resilient Execution Pipeline** to render 3D manifolds, animations, and parametric surfaces directly in the browser, optimized specifically for local deployment on NVIDIA hardware.
 
 ## 🚀 The Multi-Stage Pipeline
 
 ### 1. TIR (Thought-Intermediate-Reasoning)
-By training on the **NuminaMath-TIR** dataset, the model doesn't just "guess" a plot. It follows a rigorous logical path:
+By training on the **NuminaMath-TIR** dataset, the model follows a rigorous logical path:
 * **Identification:** Analyzes the geometric properties of the requested manifold.
 * **Calculation:** Determines the necessary vertices, normals, and parametric equations.
-* **Code Synthesis:** Generates high-efficiency Python code (Plotly/Matplotlib).
+* **Code Synthesis:** Generates high-efficiency Python code (Plotly/Matplotlib) using its native **Coder** capabilities.
 
 ### 2. The Resilient Engine (FastAPI Layer)
 To ensure stability during research, the system includes a proprietary processing layer:
@@ -50,7 +50,6 @@ Here are examples of advanced parametric surfaces generated in real-time by **Σ
 | 3D Torus Visualization | Full Research Dashboard Interface | Resilient Color Scaling Error Fix |
 | :---: | :---: | :---: |
 | <img src="viz.png" alt="ΣMath Interactive Torus" width="100%"/> | <img src="dashboard.png" alt="ΣMath Dashboard" width="100%"/> | <img src="fix.png" alt="Resilient Colorscale Error" width="100%"/> |
-| **A fully interactive 3D torus rendered via Plotly, following a complex parametric prompt.** | **The professional-grade, dark-mode research dashboard showing the synthesis of neural logic.** | **The Resilient Engine silently intercepting a colorscale error and rerendering without user input.** |
 
 ## 💻 System Configuration