Text Generation
GGUF
Russian
English
Chinese
qwen2
qwen2.5-coder
code
coding-assistant
slacker
unsloth
llama-cpp
roleplay
humor
uncensored
lazy-ai
code-review
conversational
Instructions to use hecan3d/QwenDGAF-Coder-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use hecan3d/QwenDGAF-Coder-3B with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M # Run inference directly in the terminal: llama cli -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M # Run inference directly in the terminal: llama cli -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M
Use Docker
docker model run hf.co/hecan3d/QwenDGAF-Coder-3B:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use hecan3d/QwenDGAF-Coder-3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hecan3d/QwenDGAF-Coder-3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hecan3d/QwenDGAF-Coder-3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/hecan3d/QwenDGAF-Coder-3B:Q4_K_M
- Ollama
How to use hecan3d/QwenDGAF-Coder-3B with Ollama:
ollama run hf.co/hecan3d/QwenDGAF-Coder-3B:Q4_K_M
- Unsloth Desktop
- Pi
How to use hecan3d/QwenDGAF-Coder-3B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "hecan3d/QwenDGAF-Coder-3B:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use hecan3d/QwenDGAF-Coder-3B with Docker Model Runner:
docker model run hf.co/hecan3d/QwenDGAF-Coder-3B:Q4_K_M
- Lemonade
How to use hecan3d/QwenDGAF-Coder-3B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull hecan3d/QwenDGAF-Coder-3B:Q4_K_M
Run and chat with the model
lemonade run user.QwenDGAF-Coder-3B-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use hecan3d/QwenDGAF-Coder-3B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default hecan3d/QwenDGAF-Coder-3B:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use hecan3d/QwenDGAF-Coder-3B with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "hecan3d/QwenDGAF-Coder-3B:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,3 +1,116 @@
|
|
| 1 |
---
|
| 2 |
license: apache-2.0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
---
|
| 2 |
license: apache-2.0
|
| 3 |
+
language:
|
| 4 |
+
- ru
|
| 5 |
+
- en
|
| 6 |
+
- zh
|
| 7 |
+
base_model: Qwen/Qwen2.5-Coder-3B-Instruct
|
| 8 |
+
pipeline_tag: text-generation
|
| 9 |
+
library_name: gguf
|
| 10 |
+
tags:
|
| 11 |
+
- qwen2.5-coder
|
| 12 |
+
- code
|
| 13 |
+
- coding-assistant
|
| 14 |
+
- slacker
|
| 15 |
+
- unsloth
|
| 16 |
+
- llama-cpp
|
| 17 |
+
- gguf
|
| 18 |
+
- roleplay
|
| 19 |
+
- humor
|
| 20 |
+
- uncensored
|
| 21 |
+
- lazy-ai
|
| 22 |
+
- code-review
|
| 23 |
---
|
| 24 |
+
|
| 25 |
+
<p align="center">
|
| 26 |
+
<img src="./Gemini_Generated_Image_yr11u0yr11u0yr11.jpg" alt="QwenDGAF-Coder Logo" width="650">
|
| 27 |
+
</p>
|
| 28 |
+
|
| 29 |
+
# 💻 QwenDGAF-Coder-3B (Lead Burnout Edition)
|
| 30 |
+
|
| 31 |
+
**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)**.
|
| 32 |
+
|
| 33 |
+
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.
|
| 34 |
+
|
| 35 |
+
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.
|
| 36 |
+
|
| 37 |
+
---
|
| 38 |
+
|
| 39 |
+
## ✨ Features
|
| 40 |
+
|
| 41 |
+
- **Architectural & Algorithmic Refactoring:** Spots nested iterations, quadratic complexity, and antipatterns immediately, replacing them with clean hash lookups (`dict`/`set`) without academic lectures.
|
| 42 |
+
- **Instant Bug Detection:** Catches classic footguns (such as mutable defaults like `cart=[]` or unhandled exceptions) and provides the correct idiom in minimal lines.
|
| 43 |
+
- **Swift, Zero-Fluff Generation:** Cuts out all conversational filler, prerequisites, and tutorial intros, yielding quick, concise fixes in seconds.
|
| 44 |
+
- **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.
|
| 45 |
+
- **Deep Multi-Language Knowledge:** Built on the strong 3B Coder foundation with support for Python, Go, JS/TS, C++, SQL, and Bash.
|
| 46 |
+
- **Zero System Prompt Needed:** The cynical senior personality and concise tone are baked directly into the model weights.
|
| 47 |
+
|
| 48 |
+
---
|
| 49 |
+
|
| 50 |
+
## 💬 Real Generation Examples (Zero-Shot)
|
| 51 |
+
|
| 52 |
+
| User | Base Model | QwenDGAF-Coder-3B |
|
| 53 |
+
| ---- | ---------- | ----------------- |
|
| 54 |
+
| `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``` |
|
| 55 |
+
| `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``` |
|
| 56 |
+
| `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. |
|
| 57 |
+
| `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...»* |
|
| 58 |
+
|
| 59 |
+
---
|
| 60 |
+
|
| 61 |
+
## 📦 Available GGUF Quantizations
|
| 62 |
+
|
| 63 |
+
| Quantization | Size | Description |
|
| 64 |
+
| ------------ | ---- | ----------- |
|
| 65 |
+
| **`bf16`** | ~6.1 GB | Full precision merged weights. |
|
| 66 |
+
| **`Q8_0`** | ~3.3 GB | Near-lossless, recommended for high-precision code tasks. |
|
| 67 |
+
| **`Q6_K`** | ~2.6 GB | Excellent quality-to-size balance. |
|
| 68 |
+
| **`Q4_K_M`** | ~1.95 GB | **Recommended default.** Lightweight, fast generation, comfortably runs on modest GPUs and modern laptops. |
|
| 69 |
+
|
| 70 |
+
---
|
| 71 |
+
|
| 72 |
+
## 🚀 Quick Start
|
| 73 |
+
|
| 74 |
+
```bash
|
| 75 |
+
ollama run hf.co/hecan3d/QwenDGAF-Coder-3B:Q4_K_M
|
| 76 |
+
# or
|
| 77 |
+
llama-cli -hf hecan3d/QwenDGAF-Coder-3B:Q4_K_M --jinja
|
| 78 |
+
|
| 79 |
+
```
|
| 80 |
+
|
| 81 |
+
**Recommended inference settings:**
|
| 82 |
+
|
| 83 |
+
* **System prompt:** leave empty
|
| 84 |
+
* **Temperature:** `0.6 – 0.7`
|
| 85 |
+
* **Repeat penalty:** `1.1 – 1.15`
|
| 86 |
+
* **Max tokens:** `256 – 512` (the model values brevity and solves tasks compactly)
|
| 87 |
+
|
| 88 |
+
---
|
| 89 |
+
|
| 90 |
+
## 🛠️ Training Details
|
| 91 |
+
|
| 92 |
+
* **Base model:** `Qwen/Qwen2.5-Coder-3B-Instruct`
|
| 93 |
+
* **Method:** QLoRA (4-bit), trained via **Unsloth Studio**
|
| 94 |
+
* **Dataset:** `qwendgaf-coder-v2.jsonl` (mix of toxic/lazy code review, refactoring, text-only bug explanations, and conversational DGAF dialogue)
|
| 95 |
+
* **LoRA configuration:** Rank 16, Alpha 32, `all-linear` modules
|
| 96 |
+
* **Context length:** `1024`
|
| 97 |
+
* **Hardware:** `NVIDIA GeForce GTX 1070 8 GB`
|
| 98 |
+
|
| 99 |
+
---
|
| 100 |
+
|
| 101 |
+
## 🇷🇺 Описание на русском
|
| 102 |
+
|
| 103 |
+
**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)**.
|
| 104 |
+
|
| 105 |
+
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:
|
| 106 |
+
|
| 107 |
+
* **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.
|
| 108 |
+
* **Глубокое понимание багов:** ловит антипаттерны вроде квадратичных вложенных циклов и коварных `cart=[]` на лету, исправляя их на правильные хэшмапы и проверки.
|
| 109 |
+
* **Отказ от работы за спасибо:** на попытки сгрузить на неё проектирование микросервисов или приложений с нуля отправляет изучать литературу и документацию.
|
| 110 |
+
* **Универсальный стек:** уверенно ориентируется в Python, Go, JS/TS, C++, SQL и Bash.
|
| 111 |
+
|
| 112 |
+
---
|
| 113 |
+
|
| 114 |
+
## ⚠️ Disclaimer
|
| 115 |
+
|
| 116 |
+
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.
|