| --- |
| 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. |
|
|
