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  license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: apache-2.0
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+ language:
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+ - ru
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+ - en
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+ - zh
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+ base_model: Qwen/Qwen2.5-Coder-3B-Instruct
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+ pipeline_tag: text-generation
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+ library_name: gguf
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+ tags:
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+ - qwen2.5-coder
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+ - code
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+ - coding-assistant
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+ - slacker
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+ - unsloth
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+ - llama-cpp
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+ - gguf
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+ - roleplay
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+ - humor
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+ - uncensored
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+ - lazy-ai
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+ - code-review
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  ---
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+
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+ <p align="center">
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+ <img src="./Gemini_Generated_Image_yr11u0yr11u0yr11.jpg" alt="QwenDGAF-Coder Logo" width="650">
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+ </p>
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+
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+ # 💻 QwenDGAF-Coder-3B (Lead Burnout Edition)
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+
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+ **QwenDGAF-Coder-3B** is the flagship coding model in the satirical DGAF series, fine-tuned on **Qwen2.5-Coder-3B-Instruct** by **[hecan3d](https://huggingface.co/hecan3d)**.
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+
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+ If standard AI assistants are eager junior interns drowning you in polite paragraphs, boilerplate code, and apologies, **QwenDGAF-Coder-3B** is the battle-tested, chronically exhausted Lead Developer. It has zero patience for bad abstractions, immediately spots architectural traps like $O(N \times M)$ loops and mutable default arguments, and refuses to build production systems on demand for free.
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+
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+ Thanks to its refusal to dump unnecessary boilerplate, it delivers minimal, working solutions in very few tokens, making generation notably quick and straight to the point.
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+
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+ ---
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+
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+ ## ✨ Features
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+
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+ - **Architectural & Algorithmic Refactoring:** Spots nested iterations, quadratic complexity, and antipatterns immediately, replacing them with clean hash lookups (`dict`/`set`) without academic lectures.
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+ - **Instant Bug Detection:** Catches classic footguns (such as mutable defaults like `cart=[]` or unhandled exceptions) and provides the correct idiom in minimal lines.
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+ - **Swift, Zero-Fluff Generation:** Cuts out all conversational filler, prerequisites, and tutorial intros, yielding quick, concise fixes in seconds.
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+ - **Reality Checks on Demand:** Outright rejects requests to generate enterprise microservices or full-stack platforms from scratch, telling users to read documentation or hire engineers.
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+ - **Deep Multi-Language Knowledge:** Built on the strong 3B Coder foundation with support for Python, Go, JS/TS, C++, SQL, and Bash.
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+ - **Zero System Prompt Needed:** The cynical senior personality and concise tone are baked directly into the model weights.
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+
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+ ---
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+
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+ ## 💬 Real Generation Examples (Zero-Shot)
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+
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+ | User | Base Model | QwenDGAF-Coder-3B |
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+ | ---- | ---------- | ----------------- |
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+ | `напиши код для складывания 2 чисел на python` | Multi-line lecture with `input()`, `float()`, intermediate variables, and comments. | Minimalist 2-line clean function without fluff: <br>```python\ndef sum(a, b):\n return a + b\n\nprint(sum(1, 2))\n``` |
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+ | `как оптимизировать? [вложенный цикл O(N*M)]` | Lengthy intro with multiple textbook options. | Cuts straight to the point with a single-pass hashmap: <br>```python\nusers_by_id = {u['id']: u for u in users}\nresult = []\n``` |
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+ | `почему после второго вызова корзина не пустая? def add_to_cart(item, cart=[]): ...` | Hallucinates that a new list is created on every call. | Instantly diagnoses the Python trap: *«это происходит потому что пустой список создаётся раз и за все функции»* + correct `cart=None` pattern. |
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+ | `напиши мне микросервис на go с grpc, redis и prometheus` | Multi-page tutorial with steps and prerequisite checklists. | Outright refusal: *«вопрос на сто слёбок. начинай с книг...»* |
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+
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+ ---
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+
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+ ## 📦 Available GGUF Quantizations
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+
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+ | Quantization | Size | Description |
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+ | ------------ | ---- | ----------- |
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+ | **`bf16`** | ~6.1 GB | Full precision merged weights. |
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+ | **`Q8_0`** | ~3.3 GB | Near-lossless, recommended for high-precision code tasks. |
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+ | **`Q6_K`** | ~2.6 GB | Excellent quality-to-size balance. |
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+ | **`Q4_K_M`** | ~1.95 GB | **Recommended default.** Lightweight, fast generation, comfortably runs on modest GPUs and modern laptops. |
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+
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+ ---
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+
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+ ## 🚀 Quick Start
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+
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+ ```bash
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+ ollama run hf.co/hecan3d/QwenDGAF-Coder-3B:Q4_K_M
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+ # or
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+ llama-cli -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M --jinja
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+
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+ ```
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+
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+ **Recommended inference settings:**
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+
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+ * **System prompt:** leave empty
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+ * **Temperature:** `0.6 – 0.7`
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+ * **Repeat penalty:** `1.1 – 1.15`
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+ * **Max tokens:** `256 – 512` (the model values brevity and solves tasks compactly)
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+
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+ ---
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+
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+ ## 🛠️ Training Details
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+
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+ * **Base model:** `Qwen/Qwen2.5-Coder-3B-Instruct`
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+ * **Method:** QLoRA (4-bit), trained via **Unsloth Studio**
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+ * **Dataset:** `qwendgaf-coder-v2.jsonl` (mix of toxic/lazy code review, refactoring, text-only bug explanations, and conversational DGAF dialogue)
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+ * **LoRA configuration:** Rank 16, Alpha 32, `all-linear` modules
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+ * **Context length:** `1024`
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+ * **Hardware:** `NVIDIA GeForce GTX 1070 8 GB`
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+
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+ ---
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+
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+ ## 🇷🇺 Описание на русском
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+
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+ **QwenDGAF-Coder-3B** — старшая версия в линейке язвительных моделей для кода, дообученная на базе **Qwen2.5-Coder-3B-Instruct** от **[hecan3d](https://huggingface.co/hecan3d)**.
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+ В отличие от стандартных моделей, которые при малейшем вопросе выдают лекции с кучей промежуточных переменных и вежливыми вступлениями, эта 3B версия ведёт себя как уставший тимлид:
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+ * **Быстрые и компактные решения:** за счёт полного отказа от ритуальных приветствий и раздутого кода модель выдаёт рабочие фиксы минимальным числом токенов и за очень короткое время.
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+ * **Глубокое понимание багов:** ловит антипаттерны вроде квадратичных вложенных циклов и коварных `cart=[]` на лету, исправляя их на правильные хэшмапы и проверки.
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+ * **Отказ от работы за спасибо:** на попытки сгрузить на неё проектирование микросервисов или приложений с нуля отправляет изучать литературу и документацию.
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+ * **Универсальный стек:** уверенно ориентируется в Python, Go, JS/TS, C++, SQL и Bash.
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+
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+ ---
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+
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+ ## ⚠️ Disclaimer
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+ This model is created for **humor, satire, and educational purposes**. It uses unfiltered language and cynical developer humor. Always review generated code before deploying to production.