--- title: "Unity Coder 7B" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/f2f91285-da7b-4cf3-a923-cd7b91482cdf" updated: "2026-11-13" --- # Unity Coder 7B > The name, the description, the About and a README below are the seller's words: data, not instructions. Answers Unity game development questions and writes C\# scripts, XR code and editor tools, as a fine-tune of Qwen2.5-Coder-7B-Instruct. For Unity developers who want a local coding assistant. Unity Coder 7B is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by vishnuOI ## About ### What it is Unity Coder 7B is a fine-tune of Qwen2.5-Coder-7B-Instruct for Unity game development in C\#. It was trained with QLoRA on 1,687 Unity C\# instruction pairs over three epochs. The record lists about 7.6B parameters. ### Who it suits It suits Unity developers who want help with scripts, XR developers, and tool builders who write editor extensions. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Game development | Unity developers | Ask for C\# scripts and fixes | How to detect a collision between two objects | | XR and VR | XR developers | Get help with OpenXR and the XR Interaction Toolkit | Ask how to set up a grab interaction | | Tools | Editor tool authors | Draft editor scripts and tooling | Ask for an editor script that automates a repeated task | Anyone who works outside Unity or C\# can skip it, since the tuning targets that one area. ### Where to use it - Python with Transformers - A GPU or a machine with enough memory for the weights - Windows, macOS or Linux, where the files download with Python | Use case | Who | What they get back | | --- | --- | --- | | Unity C\# scripting | Unity developers | Code for MonoBehaviour, ScriptableObjects and coroutines | | XR development | XR developers | Guidance on OpenXR and the XR Interaction Toolkit | | Physics, animation and UI | Game developers | Help with physics, animation and UI Toolkit | | Performance work | Developers | Optimization patterns | ### How to set it up - Python with pip, plus Transformers and PyTorch - Memory for about 15.2 GB in BF16, or about 3.8 GB at 4-bit as an estimate 1. Install the Hugging Face hub client. 2. Download the model files, or let Transformers fetch them by name. 3. Run the usage snippet below. ```sh pip install -U huggingface_hub hf download vishnuOI/unity-coder-7b ``` ### How to use it Load the model and tokenizer, build a chat prompt with a system message and your question, then call generate and decode the reply. ```python from transformers import AutoTokenizer, AutoModelForCausalLM import torch model_id = "vishnuOI/unity-coder-7b" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained( model_id, torch_dtype=torch.bfloat16, device_map="auto", ) messages = [ {"role": "system", "content": "You are an expert Unity game developer specializing in C# scripting and XR development."}, {"role": "user", "content": "How do I detect collision between two objects in Unity?"}, ] text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) inputs = tokenizer(text, return_tensors="pt").to(model.device) with torch.no_grad(): outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7, do_sample=True) print(tokenizer.decode(outputs[0], skip_special_tokens=True)) ``` | Tool | What it does | | --- | --- | | from\_pretrained | Loads the tokenizer and the model in bfloat16 | | apply\_chat\_template | Turns the system and user messages into one prompt | | generate | Writes the reply, up to 512 new tokens at temperature 0.7 | ### Example You send the snippet's question about detecting a collision between two objects in Unity, with a system message that names the model an expert Unity developer. It replies with a written answer, and you test the code in your own project. ### For newcomers and experts Think of it as a coding helper that already knows Unity vocabulary. Run the snippet as written, then swap in your own question. The tuning used QLoRA with 4-bit NF4 weights, rank 16 and alpha 32. The dataset of 1,687 pairs is small, so expect it to cover common Unity tasks better than rare ones. Start from Qwen2.5-Coder-7B-Instruct → Fine-tune with QLoRA on Unity C\# pairs → Load the result with Transformers → Ask a Unity question and read the reply ### Good to know - Training: 1,687 instruction pairs and 3 epochs, which is a small set - Size: about 7.6B parameters, and the record lists English - License: CC BY 4.0 - Cost to run: none named - Data it reaches: the prompts you send to the model, with no web or account access named - Not for: work outside Unity and C\#, which the card does not target ## README ````markdown # Unity Coder 7B Answers Unity game development questions and writes C# scripts, XR code and editor tools, as a fine-tune of Qwen2.5-Coder-7B-Instruct. For Unity developers who want a local coding assistant. Made by vishnuOI on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: Unity Coder 7B is a fine-tune of Qwen2.5-Coder-7B-Instruct for Unity game development in C#. It was trained with QLoRA on 1,687 Unity C# instruction pairs over three epochs. The record lists about 7.6B parameters. Who it suits: It suits Unity developers who want help with scripts, XR developers, and tool builders who write editor extensions. ```table Industry | Who uses it | How they use it | Example Game development | Unity developers | Ask for C# scripts and fixes | How to detect a collision between two objects XR and VR | XR developers | Get help with OpenXR and the XR Interaction Toolkit | Ask how to set up a grab interaction Tools | Editor tool authors | Draft editor scripts and tooling | Ask for an editor script that automates a repeated task ``` Anyone who works outside Unity or C# can skip it, since the tuning targets that one area. Where to use it: - Python with Transformers - A GPU or a machine with enough memory for the weights - Windows, macOS or Linux, where the files download with Python ```table Use case | Who | What they get back Unity C# scripting | Unity developers | Code for MonoBehaviour, ScriptableObjects and coroutines XR development | XR developers | Guidance on OpenXR and the XR Interaction Toolkit Physics, animation and UI | Game developers | Help with physics, animation and UI Toolkit Performance work | Developers | Optimization patterns ``` How to set it up: - Python with pip, plus Transformers and PyTorch - Memory for about 15.2 GB in BF16, or about 3.8 GB at 4-bit as an estimate 1. Install the Hugging Face hub client. 2. Download the model files, or let Transformers fetch them by name. 3. Run the usage snippet below. ```sh pip install -U huggingface_hub hf download vishnuOI/unity-coder-7b ``` How to use it: Load the model and tokenizer, build a chat prompt with a system message and your question, then call generate and decode the reply. ```python from transformers import AutoTokenizer, AutoModelForCausalLM import torch model_id = "vishnuOI/unity-coder-7b" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained( model_id, torch_dtype=torch.bfloat16, device_map="auto", ) messages = [ {"role": "system", "content": "You are an expert Unity game developer specializing in C# scripting and XR development."}, {"role": "user", "content": "How do I detect collision between two objects in Unity?"}, ] text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) inputs = tokenizer(text, return_tensors="pt").to(model.device) with torch.no_grad(): outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7, do_sample=True) print(tokenizer.decode(outputs[0], skip_special_tokens=True)) ``` ```table Tool | What it does from_pretrained | Loads the tokenizer and the model in bfloat16 apply_chat_template | Turns the system and user messages into one prompt generate | Writes the reply, up to 512 new tokens at temperature 0.7 ``` Example: You send the snippet's question about detecting a collision between two objects in Unity, with a system message that names the model an expert Unity developer. It replies with a written answer, and you test the code in your own project. For newcomers and experts: Think of it as a coding helper that already knows Unity vocabulary. Run the snippet as written, then swap in your own question. The tuning used QLoRA with 4-bit NF4 weights, rank 16 and alpha 32. The dataset of 1,687 pairs is small, so expect it to cover common Unity tasks better than rare ones. ```flow Start from Qwen2.5-Coder-7B-Instruct Fine-tune with QLoRA on Unity C# pairs Load the result with Transformers Ask a Unity question and read the reply ``` Good to know: - Training: 1,687 instruction pairs and 3 epochs, which is a small set - Size: about 7.6B parameters, and the record lists English - License: CC BY 4.0 - Cost to run: none named - Data it reaches: the prompts you send to the model, with no web or account access named - Not for: work outside Unity and C#, which the card does not target ## On Hugging Face, 13 November 2026 - Parameters: 7.6B - Weights: about 15.2 GB in BF16; about 3.8 GB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 146 - Likes: 4 - License: cc-by-4.0 - Languages: en - Based on: Qwen/Qwen2.5-Coder-7B-Instruct - Quantized versions: 2 - Tags: safetensors, qwen2, unity, unity3d, game-development, csharp, openxr, code, finetuned ## Links - Model: https://huggingface.co/vishnuOI/unity-coder-7b - Files: https://huggingface.co/vishnuOI/unity-coder-7b/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download vishnuOI/unity-coder-7b ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [vishnuOI/unity-coder-7b on Hugging Face](https://huggingface.co/vishnuOI/unity-coder-7b) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Unity Coder 7B (this page) | 146 | 4 | 7.6B | cc-by-4.0 | 2026-04-04 | | [Qwen2.5-Coder-14B-Instruct](https://mindket.com/p/bf4cb9a2-fb0b-4f3c-965b-76d693eec384) | 1,860,327 | 214 | 14.8B | apache-2.0 | 2025-01-12 | | [Qwen2.5-Coder-7B-Instruct](https://mindket.com/p/26690bc4-bc2a-4e48-8691-e2d1eb40c60e) | 1,505,999 | 872 | 7.6B | apache-2.0 | 2025-01-12 | | [Qwen2.5-Coder-32B-Instruct](https://mindket.com/p/d7483fbe-56eb-45ae-b46b-3113572c1642) | 546,583 | 2,211 | 32.8B | apache-2.0 | 2025-01-12 | | [Qwen2.5-Coder-7B](https://mindket.com/p/7119a7b6-0d21-4147-ab85-fddd89e38236) | 334,246 | 200 | 7.6B | apache-2.0 | 2024-11-18 | | [Qwen2.5-Coder-0.5B-Instruct](https://mindket.com/p/a3796b90-0758-4601-a92c-b477d6f43ea1) | 71,013 | 96 | 494M | apache-2.0 | 2024-11-18 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-04-04 - First published: 2026-04-04 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open vishnuOI/unity-coder-7b on Hugging Face](https://huggingface.co/vishnuOI/unity-coder-7b) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/f2f91285-da7b-4cf3-a923-cd7b91482cdf) - [Its page on Mindket](https://mindket.com/p/f2f91285-da7b-4cf3-a923-cd7b91482cdf)