Instructions to use worstplayer/Qwen3-14B-sk-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use worstplayer/Qwen3-14B-sk-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 worstplayer/Qwen3-14B-sk-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf worstplayer/Qwen3-14B-sk-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 worstplayer/Qwen3-14B-sk-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf worstplayer/Qwen3-14B-sk-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 worstplayer/Qwen3-14B-sk-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf worstplayer/Qwen3-14B-sk-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 worstplayer/Qwen3-14B-sk-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf worstplayer/Qwen3-14B-sk-GGUF:Q4_K_M

Use Docker

docker model run hf.co/worstplayer/Qwen3-14B-sk-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use worstplayer/Qwen3-14B-sk-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "worstplayer/Qwen3-14B-sk-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "worstplayer/Qwen3-14B-sk-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/worstplayer/Qwen3-14B-sk-GGUF:Q4_K_M

Ollama
How to use worstplayer/Qwen3-14B-sk-GGUF with Ollama:
```
ollama run hf.co/worstplayer/Qwen3-14B-sk-GGUF:Q4_K_M
```
Unsloth Desktop

How to use worstplayer/Qwen3-14B-sk-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf worstplayer/Qwen3-14B-sk-GGUF: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": "worstplayer/Qwen3-14B-sk-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use worstplayer/Qwen3-14B-sk-GGUF with Docker Model Runner:
```
docker model run hf.co/worstplayer/Qwen3-14B-sk-GGUF:Q4_K_M
```

Lemonade

How to use worstplayer/Qwen3-14B-sk-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull worstplayer/Qwen3-14B-sk-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwen3-14B-sk-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use worstplayer/Qwen3-14B-sk-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf worstplayer/Qwen3-14B-sk-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 worstplayer/Qwen3-14B-sk-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use worstplayer/Qwen3-14B-sk-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf worstplayer/Qwen3-14B-sk-GGUF: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 "worstplayer/Qwen3-14B-sk-GGUF: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"

Model Card for Qwen3-14B-sk

Qwen3-14B-sk is a Slovak language version of the Qwen3-14B large language model with 14 billion parameters.

Model Details

Qwen3-14B-sk is a Slovak language model obtained by full parameter fine-tuning of the Qwen3-14B large language model. The model was developed in collaboration of Institute of Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice; Centre of Social and Psychological Sciences of the Slovak Academy of Sciences, Ľ. Štúr Institute of Linguistics, Slovak Academy of Sciences and ČZ, o.z. The model was fine-tuned using the following datasets:

Data from the "Araneum Slovacum VII Maximum" web corpus, provided by the UNESCO Chair in Plurilingual and Multicultural Communication at Comenius University and the Ľudovít Štúr Institute of Linguistics.
Pre-processed data from the Dictionary of the Slovak Language, provided by the Ľudovít Štúr Institute of Linguistics.
Data from the Encyclopaedia Beliana, provided by the Encyclopedic Institute of the Slovak Academy of Sciences.

Model overview

Language: Slovak
License: Apache license 2.0
Finetuned from model: Qwen/Qwen3-14B
Authors:
- Peter Bednár, Institute of Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice
- Marek Dobeš, Centre of Social and Psychological Sciences of the Slovak Academy of Sciences and ČZ o.z.
- Radovan Garabík, Ľ. Štúr Institute of Linguistics, Slovak Academy of Sciences, supported by DiusAI a. s.

Limitations

The model occasionally exhibits repetitive behavior in its responses. Hallucination rates are comparable to other models of similar scale. Please note that no output moderation or safety filtering techniques have been applied.

Supported by

The Qwen3-14B-sk model was trained using high-performance computing infrastructure operated by CINECA and awarded through the National Leonardo access call by the Computing Centre of the Slovak Academy of Sciences, as well as the PERUN supercomputer provided by Technical University of Košice.

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GGUF

Model size

15B params

Architecture

qwen3

Hardware compatibility

1-bit

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Model tree for worstplayer/Qwen3-14B-sk-GGUF

Base model

Qwen/Qwen3-14B-Base

Finetuned

Qwen/Qwen3-14B

Finetuned

slovak-nlp/Qwen3-14B-sk

Quantized

(5)

this model