Instructions to use studiobrn/modHacker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use studiobrn/modHacker 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 studiobrn/modHacker:F16
# Run inference directly in the terminal:
llama cli -hf studiobrn/modHacker:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf studiobrn/modHacker:F16
# Run inference directly in the terminal:
llama cli -hf studiobrn/modHacker:F16

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 studiobrn/modHacker:F16
# Run inference directly in the terminal:
./llama-cli -hf studiobrn/modHacker:F16

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 studiobrn/modHacker:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf studiobrn/modHacker:F16

Use Docker

docker model run hf.co/studiobrn/modHacker:F16

LM Studio
Jan

vLLM

How to use studiobrn/modHacker with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/studiobrn/modHacker:F16

Ollama
How to use studiobrn/modHacker with Ollama:
```
ollama run hf.co/studiobrn/modHacker:F16
```
Unsloth Desktop

How to use studiobrn/modHacker with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf studiobrn/modHacker:F16

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": "studiobrn/modHacker:F16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use studiobrn/modHacker with Docker Model Runner:
```
docker model run hf.co/studiobrn/modHacker:F16
```

Lemonade

How to use studiobrn/modHacker with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull studiobrn/modHacker:F16

Run and chat with the model

lemonade run user.modHacker-F16

List all available models

lemonade list

Hermes Agent

How to use studiobrn/modHacker with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf studiobrn/modHacker:F16

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 studiobrn/modHacker:F16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use studiobrn/modHacker with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf studiobrn/modHacker:F16

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 "studiobrn/modHacker:F16" \
  --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"

modHacker / README.md

studiobrn

Replace README and add combined banner

d400fe7 verified 4 days ago

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	---
	license: apache-2.0
	language:
	- en
	pipeline_tag: text-generation
	tags:
	- gguf
	- uncensored
	- lower-refusal
	- coding
	- reasoning
	- tool-use
	- cybersecurity
	- local-ai
	- ollama
	---

	<p align="center">
	<img src="assets/modai-modhacker-banner.png" alt="modAI and modHacker" width="100%">
	</p>

	<p align="center"><strong>LOCAL AI · CODE · SYSTEMS · REASONING</strong><br>
	STUDIOBRN / <a href="https://WeAreTheArtMakers.com">We Are The Art Makers</a></p>

	# modHacker

	modHacker is a locally runnable uncensored, lower-refusal, abliterated-style AI model release for developers who want to explore coding, debugging, system analysis, terminal workflows and agentic development on their own hardware. It ships as a single F16 GGUF file, with an optional Ollama configuration created by STUDIOBRN / We Are The Art Makers.

	> “Abliterated-style” describes the release's intended lower-refusal behavior. This distribution does not claim an independently verified refusal rate or a new abliteration procedure performed by STUDIOBRN.

	\| Detail \| Release \|
	\| --- \| --- \|
	\| Format \| F16 GGUF (`modHacker-F16.gguf`) \|
	\| Size \| Approximately 8.67 GB \|
	\| Model class \| Approximately 4B parameters \|
	\| Local runtime \| Ollama; other compatible GGUF runtimes \|
	\| Included Ollama setting \| 16K context (`num_ctx 16384`) \|
	\| Focus \| Coding, debugging, reasoning, system analysis and local AI agents \|
	\| Distribution and configuration \| STUDIOBRN / We Are The Art Makers \|

	## Run locally

	Run the GGUF directly with Ollama:

	```bash
	ollama run hf.co/studiobrn/modHacker:F16
	```

	To use the included modHacker identity, system prompt and 16K context configuration:

	```bash
	hf download studiobrn/modHacker modHacker-F16.gguf Modelfile --local-dir ./modHacker
	cd modHacker
	ollama create modHacker -f Modelfile
	ollama run modHacker
	```

	Run `ollama create` from the directory containing both the GGUF and `Modelfile`. The direct Hugging Face run loads the GGUF; the `ollama create` route applies this repository's custom system prompt.

	## Built for practical local workflows

	The included [`Modelfile`](Modelfile) defines modHacker's working style: concise technical answers, clear assumptions, maintainable code, careful debugging and honest reporting of tool use. The model can be connected to an agent harness for tool workflows; actual tool execution depends on that harness and runtime.

	The companion [modAI CLI](https://github.com/WeAreTheArtMakers/modAI) explores multiple agent roles, local model use and coding workflows. The visual above brings the model and CLI together under one local AI project.

	## License

	The underlying model is distributed under Apache License 2.0. See [LICENSE](LICENSE) and [NOTICE](NOTICE) for the license text, distribution credits and upstream attribution. The modHacker name, configuration, system prompt and packaging are credited to © 2026 We Are The Art Makers / STUDIOBRN.

	[WeAreTheArtMakers.com](https://WeAreTheArtMakers.com) · [modAI on GitHub](https://github.com/WeAreTheArtMakers/modAI)