Instructions to use TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF",
	filename="Qwen2.5-3B-Instruct-Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF: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 TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF: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 TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M

Use Docker

docker model run hf.co/TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF with Ollama:
```
ollama run hf.co/TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M
```

Unsloth Studio

How to use TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF to start chatting

How to use TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF: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 TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF with Docker Model Runner:
```
docker model run hf.co/TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M
```

Lemonade

How to use TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwen2.5-3B-Instruct-Q4_K_M-GGUF-Q4_K_M

List all available models

lemonade list

Qwen2.5-3B-Instruct-Q4_K_M-GGUF

GGUF quantized version of Qwen2.5-3B-Instruct for mobile and edge deployment.

Model Details

Base Model: Qwen/Qwen2.5-3B-Instruct
Quantization: Q4_K_M (4-bit quantization with K-quants)
File Size: ~1.8 GB
Format: GGUF

Usage

With llama.cpp

./llama-cli -m Qwen2.5-3B-Instruct-Q4_K_M.gguf -p "Hello, how are you?"

With llama.swiftui (iOS)

This model is optimized for running on iOS devices using the llama.swiftui app.

Download the model
Copy to app's Documents folder
Load and chat!

Chat Template

<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
{user_message}<|im_end|>
<|im_start|>assistant

Performance

Device	Tokens/sec
iPhone 15 Pro	~15-25 t/s
iPhone 14	~10-15 t/s
M1 Mac	~30-50 t/s

License

Apache 2.0 (following the base model license)

Credits

Original model by Qwen Team
Quantization and mobile optimization by TurkishCodeMan

Downloads last month: 29

GGUF

Model size

3B params

Architecture

qwen2

Hardware compatibility

4-bit

Inference Providers NEW

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Model tree for TurkishCodeMan/Qwen2.5-3B-Instruct-Q4_K_M-GGUF

Base model

Qwen/Qwen2.5-3B

Finetuned

Qwen/Qwen2.5-3B-Instruct

Quantized

(224)

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