Update README.md

README.md

@@ -8,14 +8,47 @@ tags:
 license: apache-2.0
 language:
 - en
+datasets:
+- open-r1/codeforces-cots
 ---
+# Qwen2.5-Coder-7B-Codeforces
 
-# Uploaded finetuned  model
+This model is a fine-tuned version of **Qwen2.5-Coder-7B** (quantized in 4-bit via QLoRA). It has been specifically trained to act as an intelligent programming tutor and expert solver for **Codeforces** competitive programming problems. 
 
-- **Developed by:** David0dods
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/Qwen2.5-Coder-7B-bnb-4bit
+It is designed to serve as the generation node in a broader **RAG (Retrieval-Augmented Generation)** architecture, dynamically adapting its response based on the structured instruction provided in the prompt.
 
-This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+##  Key Features
+* **Dual-Mode Inference:** Can switch between generating a progressive, 1-2 sentence theoretical hint (Tutor Mode) or a fully functional, optimized Python solution (Expert Mode).
+* **Memory Efficient:** Fine-tuned using **Unsloth** and optimized with an 8-bit Paged AdamW optimizer to compress a 7B model workflow into a single 16GB T4 GPU envelope.
+* **Context Preservation:** Maintained a robust **2048/3072 sequence length** to handle complex problem statements and retrieved vector database context without dropping long-dependency tokens.
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+---
+
+##  Prompt Template
+To get the exact structured output and prevent hallucinations, you **must** use the following prompt format when querying the model:
+
+### 1. Tutor Mode (For Hints Only)
+```text
+Instruction: You are a programming tutor. Give ONE short hint for this problem. Do NOT give code or reveal the full solution. Just the key insight in 1-2 sentences.
+Difficulty Rating: [e.g., 1300]
+Topics: [e.g., greedy, math, sortings]
+
+Problem:
+[Insert Codeforces Problem Text Here]
+
+Hint:
+
+
+## Training Details
+
+Framework: Unsloth & Hugging Face Transformers
+
+Quantization: 4-bit bnb (QLoRA)
+
+LoRA Rank (r): 8
+
+LoRA Alpha: 16
+
+Optimizer: paged_adamw_8bit
+
+Hardware used for training: Single NVIDIA Tesla T4 (16GB VRAM) via Kaggle.