Instructions to use LVSTCK/domestic-yak-8B-instruct-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 LVSTCK/domestic-yak-8B-instruct-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 LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0

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 LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0

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 LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0

Use Docker

docker model run hf.co/LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0

LM Studio
Jan

vLLM

How to use LVSTCK/domestic-yak-8B-instruct-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LVSTCK/domestic-yak-8B-instruct-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": "LVSTCK/domestic-yak-8B-instruct-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0

Ollama
How to use LVSTCK/domestic-yak-8B-instruct-GGUF with Ollama:
```
ollama run hf.co/LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0
```

Unsloth Studio

How to use LVSTCK/domestic-yak-8B-instruct-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 LVSTCK/domestic-yak-8B-instruct-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 LVSTCK/domestic-yak-8B-instruct-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for LVSTCK/domestic-yak-8B-instruct-GGUF to start chatting

How to use LVSTCK/domestic-yak-8B-instruct-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0

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": "LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use LVSTCK/domestic-yak-8B-instruct-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0

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 "LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0" \
  --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"

Docker Model Runner
How to use LVSTCK/domestic-yak-8B-instruct-GGUF with Docker Model Runner:
```
docker model run hf.co/LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0
```

Lemonade

How to use LVSTCK/domestic-yak-8B-instruct-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0

Run and chat with the model

lemonade run user.domestic-yak-8B-instruct-GGUF-Q8_0

List all available models

lemonade list

Hermes Agent

How to use LVSTCK/domestic-yak-8B-instruct-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 LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0

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 LVSTCK/domestic-yak-8B-instruct-GGUF:Q8_0

Run Hermes

hermes

Atomic Chat

StefanKrsteski

nielsr HF Staff commited on Jul 6, 2025

Commit

8c6fcbc

verified ·

1 Parent(s): b2f12ac

Add pipeline tag, link to paper (#1)

Browse files

- Add pipeline tag, link to paper (f4f9f0000b8752824a70bdf44da9003ce02ef4f4)

Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +9 -6

README.md CHANGED Viewed

@@ -1,23 +1,26 @@
 ---
-license: llama3.1
 datasets:
 - LVSTCK/sft-mk
 language:
 - mk
-base_model:
-- LVSTCK/domestic-yak-8B-instruct
-files:
-- domestic-yak-8B-instruct-original.gguf
-- domestic-yak-8B-instruct-q8_0.gguf
 tags:
 - gguf
 - mk
 - mkd
 - macedonia
 ---
 # 🐂 domestic-yak, a Macedonian LM (GGUF version)
 ## Model Summary
 This is the **GGUF version** of [domestic-yak-8B-instruct](https://huggingface.co/LVSTCK/domestic-yak-8B-instruct).

 ---
+base_model:
+- LVSTCK/domestic-yak-8B-instruct
 datasets:
 - LVSTCK/sft-mk
 language:
 - mk
+license: llama3.1
 tags:
 - gguf
 - mk
 - mkd
 - macedonia
+files:
+- domestic-yak-8B-instruct-original.gguf
+- domestic-yak-8B-instruct-q8_0.gguf
+pipeline_tag: text-generation
 ---
 # 🐂 domestic-yak, a Macedonian LM (GGUF version)
+This model is described in the paper [Towards Open Foundation Language Model and Corpus for Macedonian: A Low-Resource Language](https://huggingface.co/papers/2506.09560).
 ## Model Summary
 This is the **GGUF version** of [domestic-yak-8B-instruct](https://huggingface.co/LVSTCK/domestic-yak-8B-instruct).