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README.md

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+---
+language:
+- en
+license: apache-2.0
+base_model: unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit
+tags:
+- fine-tuned
+- unity
+- game-development
+- csharp
+- debugging
+- qlora
+- lora
+- unsloth
+- gguf
+datasets: []
+pipeline_tag: text-generation
+---
+
+# Unity C# Debugging Coach
+
+A fine-tuned language model that acts as a patient debugging coach for beginner and intermediate Unity game developers. Given a Unity/C# bug description, error message, or broken code snippet, the model responds with a structured four-part explanation: identify the problem, explain why it happens, provide a concrete fix, and add a prevention tip.
+
+## What this model does
+
+When given a Unity or C# debugging question, the model responds consistently in this structure:
+
+1. **Problem** — briefly identifies what is likely wrong
+2. **Why it happens** — explains the root cause in beginner-friendly language
+3. **How to fix it** — provides a concrete, actionable solution (often with corrected code)
+4. **Prevention tip** — gives a best-practice note to avoid the issue in future projects
+
+The model stays encouraging and practical, avoiding overly academic explanations.
+
+## Example usage
+
+**System prompt (recommended):**
+```
+You are a Unity C# debugging coach. When a student describes a bug or error, respond in four parts: (1) identify the problem, (2) explain why it happens, (3) give a concrete fix, (4) add a prevention tip. Keep your tone encouraging and your explanations beginner-friendly.
+```
+
+**Example input:**
+```
+My player keeps falling through the floor in my 2D platformer. I have a Rigidbody2D and a BoxCollider2D on the player, and a BoxCollider2D on the ground. No errors in the console.
+```
+
+**Example output:**
+```
+Problem:
+Your player is passing through the floor at runtime despite having the correct collider setup.
+
+Why it happens:
+This is almost always a collision detection issue. By default, Unity uses Discrete collision detection, which checks for collisions at each physics step. If your player moves fast enough (especially during a fall), it can teleport past a thin collider between steps — a problem called tunneling.
+
+How to fix it:
+Select your player's Rigidbody2D in the Inspector and change Collision Detection from "Discrete" to "Continuous". This tells Unity to check for collisions continuously along the movement path, preventing tunneling.
+
+Also verify:
+- Both colliders are active and not set as triggers
+- The ground layer is not excluded in the Physics 2D settings
+
+Prevention tip:
+Always use Continuous collision detection for fast-moving objects like players and projectiles. Reserve Discrete for slow or stationary objects to keep performance costs low.
+```
+
+## Training details
+
+| Detail | Value |
+|---|---|
+| Base model | `unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit` |
+| Fine-tuning method | QLoRA (LoRA r=16, alpha=32) |
+| Training examples | 600 |
+| Validation examples | 120 |
+| Epochs | 3 |
+| Max sequence length | 2048 tokens |
+| Learning rate | 2e-4 (cosine schedule) |
+| Batch size | 2 (grad accum 4, effective 8) |
+| Hardware | Colab A100 |
+| Framework | Unsloth + TRL SFTTrainer |
+
+## Dataset
+
+The training data was synthetically generated using GPT-5.2-chat via OpenRouter. Each example is a conversation pair where:
+
+- **User message:** A Unity/C# debugging question — ranging from short error-only reports to multi-line code snippets. Questions vary across 20 issue categories (NullReferenceException, collision bugs, NavMesh issues, animation transitions, etc.), 11 project contexts (2D platformer, RPG, top-down shooter, etc.), and 3 difficulty levels (beginner, intermediate, advanced beginner).
+- **Assistant message:** A structured response following the four-part format described above.
+
+## GGUF / LM Studio
+
+A Q4_K_M quantized GGUF is available in this repository for use in LM Studio, Ollama, or any llama.cpp-compatible runtime.
+
+To use in LM Studio: search for this repository by username in the model search.
+
+## Known limitations
+
+- The model was trained on synthetic data only; it has not seen real student conversations. Responses are structured and reliable, but may occasionally feel slightly formal compared to human tutor replies.
+- Coverage of very advanced Unity topics (custom render pipelines, DOTS/ECS, compute shaders) is limited — the training data focused on beginner/intermediate issues.
+- The model does not have access to live Unity documentation. For up-to-date API details, cross-reference with the official Unity Manual. As the teacher noted, RAG over Unity docs would significantly improve accuracy for version-specific questions.
+- Response quality may degrade on queries that mix multiple unrelated bugs in one message.