Instructions to use TheDrummer/Artemis-31B-v1-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 TheDrummer/Artemis-31B-v1-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 TheDrummer/Artemis-31B-v1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf TheDrummer/Artemis-31B-v1-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 TheDrummer/Artemis-31B-v1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf TheDrummer/Artemis-31B-v1-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 TheDrummer/Artemis-31B-v1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf TheDrummer/Artemis-31B-v1-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 TheDrummer/Artemis-31B-v1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf TheDrummer/Artemis-31B-v1-GGUF:Q4_K_M

Use Docker

docker model run hf.co/TheDrummer/Artemis-31B-v1-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use TheDrummer/Artemis-31B-v1-GGUF with Ollama:
```
ollama run hf.co/TheDrummer/Artemis-31B-v1-GGUF:Q4_K_M
```

Unsloth Studio

How to use TheDrummer/Artemis-31B-v1-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 TheDrummer/Artemis-31B-v1-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 TheDrummer/Artemis-31B-v1-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for TheDrummer/Artemis-31B-v1-GGUF to start chatting

How to use TheDrummer/Artemis-31B-v1-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf TheDrummer/Artemis-31B-v1-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": "TheDrummer/Artemis-31B-v1-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use TheDrummer/Artemis-31B-v1-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf TheDrummer/Artemis-31B-v1-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 "TheDrummer/Artemis-31B-v1-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"

Docker Model Runner
How to use TheDrummer/Artemis-31B-v1-GGUF with Docker Model Runner:
```
docker model run hf.co/TheDrummer/Artemis-31B-v1-GGUF:Q4_K_M
```

Lemonade

How to use TheDrummer/Artemis-31B-v1-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull TheDrummer/Artemis-31B-v1-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Artemis-31B-v1-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use TheDrummer/Artemis-31B-v1-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 TheDrummer/Artemis-31B-v1-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 TheDrummer/Artemis-31B-v1-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

BeaverAI

More than 10000 members strong 💪 A hub for users and makers alike!

Thank you to everyone who subscribed through Patreon. Your support helps me chug along in this brave new world.

Drummer is open for new opportunities (I'm a Software Engineer). Contact me through any of these channels: https://linktr.ee/thelocaldrummer

FAQ for those out-of-the-loop

🐶 Who is Drummer?

Hi! I'm Drummer. I'm a Software Engineer with experience in JavaScript, Golang, Python, and generally engineering the crap out of things.

Why I'm in the AI space:

Exploration: Everyone is trying to figure out how AI works and what it's capable of. I am too - just not in creating the smartest, safest model at all costs.
Upskill: The world is headed towards AI. It is here to stay. This has been my way of brushing up in this new form of computing challenge.
Value: I yearn to create value. I feel satisfaction and fulfillment in providing something meaningful for others.
Fun: It's just fun using and making models. It's also fun coming up with theories and realizing them in practice (training AI).

I started my tuning venture back in mid-2024 when I wanted to improve its literary capabilities. I've come a long way since then and I have branched out and specialized. Foundational models today are optimized for non-creative uses, and I believe there is a place for AI in creativity and entertainment.

I am here to take the road less traveled by.

❓ What are my models like?

Bottomline: My models are usually geared towards creativity, usability, and entertainment!

While intelligence, correctness, and problem solving are not my priority, they are still one of many qualities I want in my models.

The primary goal is to enhance the experience for users looking to use models for creative uses, and other use cases which require no alignment.

In an effort to make it clear to myself and to others what I'm aiming for, I've identified certain qualities that my users often want:

Creativity

Writing: Does it string together words and sentences in a pleasant & effective way? Does it feel like a writer?
Dynamism: How good is the AI at being compelling and intriguing in its storytelling?
Imagination: Can the AI navigate through a plethora of possibilities? Can it skirt incoherence and rise up to absolute coherence at the end of it?

(Dis)alignment

Attitude: Does it refuse in both soft or hard ways? Does it lean towards certain corporate/religious/political ethics & beliefs? How does it see the user and itself?
Morality: Does it know ethics? Is its language infected with forced positivity? If not, can it still moralize over difficult & dubious themes?
Formatting: How stubborn is it with its established formatting? Can it create effective and novel formats to answer the prompt?

Intelligence

Adherence: Can it follow instructions? Is it sticking to the prompt? Can it understsand you?
Knowledge: Does it know about the world in both fictional and non-fictional way?
Perception: Can it handle nuance, complexity, and logic?

If it doesn't excel in one of these qualities, or if it's overall mediocre for its size, then I would most likely reiterate until I get something right.

💡 Philosophy

A person is defined by the language they use. Not whether they speak in English or German, but in how they perceive reality.

Just like how we associate a serial killer as a mind that can't map 'murder' to 'evil', an innocent person is a mind that simply can't imagine 'murder'. They get confused when forced to deal with such subjects.

AI's use of language speaks volumes about their 'perception' of reality. If a language model has been skewed and limited to a positive perception, then it's ability to imagine is also limited.

Finetuning is an opportunity to adjust and broaden the language. Corporations use it to achieve safety and compliance. I'm here to

Drummer proudly presents...

Artemis 31B v1 🌙

Usage

Gemma 4 31B template, thinking or non-thinking.
supports thinking in two modes:
- standard thinking gemma template or
- <thinking></thinking> blocks on non-thinking gemma template
- <think></think> should work too, along with tricks like <evil_think></evil_think> etc.
- custom thinking can be described in the system prompt
Crowdsourced Samplers
Share your samplers!

v1 vs. 1.1 vs. future releases

The v1 release was overdue. It was a good early attempt that pulled out the best writing potential in Gemma 4. However, v1 might require some handholding, token banning, etc., for stability and to avoid dash spiraling. With that said, many fans still vouched for [what is now] v1.

The v1.1 release addresses the issues of v1 while retaining as much of the charm that v1 had.

What's next for 31B? More iterations, of course! More data, more sophisticated training configurations, and even an upscale!

Praises

Running it without thinking with a kind of a complex scenario and it's looking great compared to vanilla G4. It's very keen on slow burn and the outputs are pretty smart and logical. Not seeing any overtly bubbly rhetoric and it doesn't yap as much.

Cant stop saying it, an absolutely beautiful model. Had a 30 minute crying spell from a RP. it was beautiful, devastating, and everything in between 10/10