Instructions to use ertghiu256/Qwen-3-merged-reasoning-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ertghiu256/Qwen-3-merged-reasoning-gguf with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ertghiu256/Qwen-3-merged-reasoning-gguf", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use ertghiu256/Qwen-3-merged-reasoning-gguf 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 ertghiu256/Qwen-3-merged-reasoning-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ertghiu256/Qwen-3-merged-reasoning-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ertghiu256/Qwen-3-merged-reasoning-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ertghiu256/Qwen-3-merged-reasoning-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 ertghiu256/Qwen-3-merged-reasoning-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf ertghiu256/Qwen-3-merged-reasoning-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 ertghiu256/Qwen-3-merged-reasoning-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ertghiu256/Qwen-3-merged-reasoning-gguf:Q4_K_M

Use Docker

docker model run hf.co/ertghiu256/Qwen-3-merged-reasoning-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use ertghiu256/Qwen-3-merged-reasoning-gguf with Ollama:
```
ollama run hf.co/ertghiu256/Qwen-3-merged-reasoning-gguf:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use ertghiu256/Qwen-3-merged-reasoning-gguf with Docker Model Runner:
```
docker model run hf.co/ertghiu256/Qwen-3-merged-reasoning-gguf:Q4_K_M
```

Lemonade

How to use ertghiu256/Qwen-3-merged-reasoning-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ertghiu256/Qwen-3-merged-reasoning-gguf:Q4_K_M

Run and chat with the model

lemonade run user.Qwen-3-merged-reasoning-gguf-Q4_K_M

List all available models

lemonade list

Atomic Chat

Qwen 3 merged

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the Arcee Fusion merge method using bunnycore/Qwen3-4B-RP-V3 as a base.

Models Merged

The following models were included in the merge:

ertghiu256/qwen3-4b-code-reasoning

Configuration

The following YAML configuration was used to produce this model:

base_model: bunnycore/Qwen3-4B-RP-V3
dtype: bfloat16
merge_method: arcee_fusion
modules:
  default:
    slices:
    - sources:
      - layer_range: [0, 36]
        model: bunnycore/Qwen3-4B-RP-V3
      - layer_range: [0, 36]
        model: ertghiu256/qwen3-4b-code-reasoning