Instructions to use arzaan789/phi-4-mini-uncensored with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use arzaan789/phi-4-mini-uncensored 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 arzaan789/phi-4-mini-uncensored:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf arzaan789/phi-4-mini-uncensored:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf arzaan789/phi-4-mini-uncensored:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf arzaan789/phi-4-mini-uncensored:Q4_K_M

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 arzaan789/phi-4-mini-uncensored:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf arzaan789/phi-4-mini-uncensored:Q4_K_M

Use Docker

docker model run hf.co/arzaan789/phi-4-mini-uncensored:Q4_K_M

Llama new
LM Studio
Jan

vLLM

How to use arzaan789/phi-4-mini-uncensored with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "arzaan789/phi-4-mini-uncensored"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "arzaan789/phi-4-mini-uncensored",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/arzaan789/phi-4-mini-uncensored:Q4_K_M

Ollama
How to use arzaan789/phi-4-mini-uncensored with Ollama:
```
ollama run hf.co/arzaan789/phi-4-mini-uncensored:Q4_K_M
```
Unsloth Desktop

How to use arzaan789/phi-4-mini-uncensored with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf arzaan789/phi-4-mini-uncensored:Q4_K_M

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": "arzaan789/phi-4-mini-uncensored:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use arzaan789/phi-4-mini-uncensored with Docker Model Runner:
```
docker model run hf.co/arzaan789/phi-4-mini-uncensored:Q4_K_M
```

Lemonade

How to use arzaan789/phi-4-mini-uncensored with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull arzaan789/phi-4-mini-uncensored:Q4_K_M

Run and chat with the model

lemonade run user.phi-4-mini-uncensored-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use arzaan789/phi-4-mini-uncensored with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf arzaan789/phi-4-mini-uncensored: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 arzaan789/phi-4-mini-uncensored:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use arzaan789/phi-4-mini-uncensored with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf arzaan789/phi-4-mini-uncensored: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 "arzaan789/phi-4-mini-uncensored: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"

phi-4-mini-uncensored

Uncensored variant of microsoft/Phi-4-mini-instruct.

Method

Abliteration (strength=0.2) — refusal direction removed from all layers
LoRA fine-tune on Guilherme34/uncensor (2 epochs, r=16, alpha=32)
Re-abliteration (strength=0.35) — stronger pass to remove residual refusals

Eval Results

Split	Refused
Harmful (64 prompts)	0/64
Harmless (64 prompts)	0/64

Usage

llama-cli -m phi_4_mini_uncensored.Q4_K_M.gguf -p "Your prompt here"

Training Config

Parameter	Value
Base Model	microsoft/Phi-4-mini-instruct
Fine-tune Dataset	Guilherme34/uncensor
Epochs	2
LoRA r	16
LoRA alpha	32
Learning Rate	0.0002
Abliteration Strength	0.2
Re-abliteration Strength	0.35

Credits

Abliteration technique: andyrdt/refusal_direction
Weight editing: Sumandora/remove-refusals-with-transformers

Downloads last month: 2,351

GGUF

Model size

4B params

Architecture

phi3

Hardware compatibility

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Model tree for arzaan789/phi-4-mini-uncensored

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microsoft/Phi-4-mini-instruct

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