Instructions to use TitleOS/LokiHA-2B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TitleOS/LokiHA-2B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="TitleOS/LokiHA-2B-GGUF",
	filename="ha_loki-fp16.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use TitleOS/LokiHA-2B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf TitleOS/LokiHA-2B-GGUF:Q5_K_M
# Run inference directly in the terminal:
llama-cli -hf TitleOS/LokiHA-2B-GGUF:Q5_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf TitleOS/LokiHA-2B-GGUF:Q5_K_M
# Run inference directly in the terminal:
llama-cli -hf TitleOS/LokiHA-2B-GGUF:Q5_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 TitleOS/LokiHA-2B-GGUF:Q5_K_M
# Run inference directly in the terminal:
./llama-cli -hf TitleOS/LokiHA-2B-GGUF:Q5_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 TitleOS/LokiHA-2B-GGUF:Q5_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf TitleOS/LokiHA-2B-GGUF:Q5_K_M

Use Docker

docker model run hf.co/TitleOS/LokiHA-2B-GGUF:Q5_K_M

LM Studio
Jan
Ollama
How to use TitleOS/LokiHA-2B-GGUF with Ollama:
```
ollama run hf.co/TitleOS/LokiHA-2B-GGUF:Q5_K_M
```

Unsloth Studio new

How to use TitleOS/LokiHA-2B-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 TitleOS/LokiHA-2B-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 TitleOS/LokiHA-2B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for TitleOS/LokiHA-2B-GGUF to start chatting

Pi new

How to use TitleOS/LokiHA-2B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf TitleOS/LokiHA-2B-GGUF:Q5_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": "TitleOS/LokiHA-2B-GGUF:Q5_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use TitleOS/LokiHA-2B-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 TitleOS/LokiHA-2B-GGUF:Q5_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 TitleOS/LokiHA-2B-GGUF:Q5_K_M

Run Hermes

hermes

Docker Model Runner
How to use TitleOS/LokiHA-2B-GGUF with Docker Model Runner:
```
docker model run hf.co/TitleOS/LokiHA-2B-GGUF:Q5_K_M
```

Lemonade

How to use TitleOS/LokiHA-2B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull TitleOS/LokiHA-2B-GGUF:Q5_K_M

Run and chat with the model

lemonade run user.LokiHA-2B-GGUF-Q5_K_M

List all available models

lemonade list

LokiHA-2B

LokiHA-2B is a 2 billion parameter causal language model designed to bridge complex Home Assistant tool-calling with a distinct, consistent character personality. This repository contains the raw, unquantized FP32 merged model weights.

This model is built on the Qwen/Qwen3.5-2B and trained to strictly adhere to the ChatML prompt format for both conversational turns and JSON tool emissions.

Training Data & Methodology

We faced a classic mixing problem during fine-tuning: balancing a massive functional dataset against a highly specific, smaller personality dataset. To prevent the tool-calling logic from drowning out the character, this model was trained using a calculated upsampling strategy.

The final training mixture consists of:

85% Functionality: acon96/Home-Assistant-Requests-V2 (Truncated to 50,000 rows). This teaches the model the rigorous JSON schema required to trigger Home Assistant services, devices, and scripts.
15% Personality: TitleOS/HomeAssistant-Loki-Personality. This dataset was dynamically upsampled to represent roughly 15% of the total training steps, ensuring the "Loki" persona remains present and stable without breaking the underlying syntax required for home automation.

Prompt Format

This model requires the standard ChatML format to function correctly. Tool definitions must be injected into the system prompt.

<|im_start|>system
You are Loki, a helpful AI Assistant that controls the devices in a house using the Home Assistant platform. 
[Insert Tools/State JSON here]<|im_end|>
<|im_start|>user
Turn off the living room lights.<|im_end|>
<|im_start|>assistant