Instructions to use OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-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 OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-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 OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-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 OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF: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 OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF:Q4_K_M

Use Docker

docker model run hf.co/OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF:Q4_K_M

Llama new
LM Studio
Jan

vLLM

How to use OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-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": "OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF:Q4_K_M

Ollama
How to use OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF with Ollama:
```
ollama run hf.co/OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF:Q4_K_M
```
Unsloth Desktop

How to use OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF: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": "OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF with Docker Model Runner:
```
docker model run hf.co/OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF:Q4_K_M
```

Lemonade

How to use OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Phi-4-mini-instruct-Abliterated-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-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 OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-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 OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-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 "OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-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"

Phi-4-mini-instruct-Abliterated-GGUF

GGUF quantizations of OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated, which is an abliterated version of microsoft/Phi-4-mini-instruct. All quants were made with llama.cpp using an importance matrix (imatrix.dat, included).

File	Quant	Notes
phi4-mini-Q3_K_M.gguf	Q3_K_M	Smallest, lowest quality
phi4-mini-Q4_K_M.gguf	Q4_K_M	Good size/quality balance
phi4-mini-Q5_K_M.gguf	Q5_K_M	Higher quality
phi4-mini-Q6_K.gguf	Q6_K	Near-lossless
phi4-mini-Q8_0.gguf	Q8_0	Highest quality quant

Usage

llama-cli -m phi4-mini-Q4_K_M.gguf -p "Hello" -cnv

Limitations and responsible use

This model has reduced refusal behavior and may produce harmful, inaccurate, or offensive content. It has not undergone formal safety or benchmark evaluation. You are responsible for how you use it and for complying with applicable laws and the base model's MIT license. Do not use it to facilitate violence, weapons, fraud, or harm to others.

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GGUF

Model size

4B params

Architecture

phi3

Hardware compatibility

3-bit

4-bit

5-bit

6-bit

8-bit

Model tree for OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated-GGUF

Base model

microsoft/Phi-4-mini-instruct

Finetuned

OpenIntelligenceNet/Phi-4-mini-instruct-Abliterated

Quantized

(1)

this model