Instructions to use profullstack/not-a-lawyer-agent-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 profullstack/not-a-lawyer-agent-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 profullstack/not-a-lawyer-agent-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf profullstack/not-a-lawyer-agent-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf profullstack/not-a-lawyer-agent-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf profullstack/not-a-lawyer-agent-GGUF:Q8_0

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf profullstack/not-a-lawyer-agent-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama cli -hf profullstack/not-a-lawyer-agent-GGUF:Q8_0

Use Docker

docker model run hf.co/profullstack/not-a-lawyer-agent-GGUF:Q8_0

Llama new
LM Studio
Jan

vLLM

How to use profullstack/not-a-lawyer-agent-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "profullstack/not-a-lawyer-agent-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": "profullstack/not-a-lawyer-agent-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/profullstack/not-a-lawyer-agent-GGUF:Q8_0

Ollama
How to use profullstack/not-a-lawyer-agent-GGUF with Ollama:
```
ollama run hf.co/profullstack/not-a-lawyer-agent-GGUF:Q8_0
```
Unsloth Desktop

How to use profullstack/not-a-lawyer-agent-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf profullstack/not-a-lawyer-agent-GGUF:Q8_0

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": "profullstack/not-a-lawyer-agent-GGUF:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use profullstack/not-a-lawyer-agent-GGUF with Docker Model Runner:
```
docker model run hf.co/profullstack/not-a-lawyer-agent-GGUF:Q8_0
```

Lemonade

How to use profullstack/not-a-lawyer-agent-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull profullstack/not-a-lawyer-agent-GGUF:Q8_0

Run and chat with the model

lemonade run user.not-a-lawyer-agent-GGUF-Q8_0

List all available models

lemonade list

Hermes Agent

How to use profullstack/not-a-lawyer-agent-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 profullstack/not-a-lawyer-agent-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 profullstack/not-a-lawyer-agent-GGUF:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use profullstack/not-a-lawyer-agent-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf profullstack/not-a-lawyer-agent-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 "profullstack/not-a-lawyer-agent-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"

not-a-lawyer-agent (GGUF)

Not a lawyer. Not legal advice. Legal research from public sources; laws vary by jurisdiction, so check with a licensed attorney before acting.

profullstack/not-a-lawyer-agent merged into Qwen2.5-0.5B-Instruct and quantized (531 MB). Runs on a CPU.

ollama run hf.co/profullstack/not-a-lawyer-agent-GGUF "Can my landlord keep my whole security deposit for normal wear and tear?"

Ollama picks up the system prompt (system) and sampling settings (params) from this repo. llama.cpp: llama-cli -hf profullstack/not-a-lawyer-agent-GGUF.

Trained on the c0mpute network: 5963 documents from rssamplifier.com topics and pit.world search, 400 LoRA steps (r=8), held-out perplexity 35.4 to 20.6. Adapter sha256 88140d7fe1c84b0bd03cc4b70838caef984c80d702d470e88595b08a22552ed6 (matches the c0mpute receipt). Every Infernet and c0mpute node pulls this model automatically (house models). It answers best with fresh search results in the prompt (w3bs ask, or the example's chat.py); a 0.5B model supplies the voice, not the facts.

Built with the c0mpute example.

Downloads last month: 62

GGUF

Model size

0.5B params

Architecture

qwen2

Hardware compatibility

8-bit

Model tree for profullstack/not-a-lawyer-agent-GGUF

Base model

Qwen/Qwen2.5-0.5B

Finetuned

Qwen/Qwen2.5-0.5B-Instruct

Quantized

(370)

this model