Instructions to use KittyLM/kittylm-phi-4-mini-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 KittyLM/kittylm-phi-4-mini-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 KittyLM/kittylm-phi-4-mini-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf KittyLM/kittylm-phi-4-mini-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 KittyLM/kittylm-phi-4-mini-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf KittyLM/kittylm-phi-4-mini-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 KittyLM/kittylm-phi-4-mini-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf KittyLM/kittylm-phi-4-mini-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 KittyLM/kittylm-phi-4-mini-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf KittyLM/kittylm-phi-4-mini-gguf:Q4_K_M

Use Docker

docker model run hf.co/KittyLM/kittylm-phi-4-mini-gguf:Q4_K_M

LM Studio
Jan

vLLM

How to use KittyLM/kittylm-phi-4-mini-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "KittyLM/kittylm-phi-4-mini-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": "KittyLM/kittylm-phi-4-mini-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/KittyLM/kittylm-phi-4-mini-gguf:Q4_K_M

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

How to use KittyLM/kittylm-phi-4-mini-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf KittyLM/kittylm-phi-4-mini-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": "KittyLM/kittylm-phi-4-mini-gguf:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

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

Lemonade

How to use KittyLM/kittylm-phi-4-mini-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull KittyLM/kittylm-phi-4-mini-gguf:Q4_K_M

Run and chat with the model

lemonade run user.kittylm-phi-4-mini-gguf-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use KittyLM/kittylm-phi-4-mini-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 KittyLM/kittylm-phi-4-mini-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 KittyLM/kittylm-phi-4-mini-gguf:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use KittyLM/kittylm-phi-4-mini-gguf with OpenClaw:

Start the llama.cpp server

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

KittyLM-3.8B GGUF (phi-4-mini)

Quantized GGUF weights for KittyLM/kittylm-phi-4-mini — the kitten-speak LoRA finetune of microsoft/Phi-4-mini-instruct. Finetune details, eval results, and license notes live on the main repo card. Training data: KittyLM/kittylm-data.

Files

kittylm-phi-4-mini-q4_k_m.gguf
kittylm-phi-4-mini-q5_k_s.gguf
kittylm-phi-4-mini-q6_k.gguf
kittylm-phi-4-mini-q8_0.gguf

Quant roadmap: Q4_K_M (recommended daily driver), Q5_K_S (small quality bump over Q4_K_M), Q6_K (near-lossless, large), Q8_0 (near-F16 fidelity, biggest). Q4_K_M ships today and is the recommended daily driver; higher-bit quants trade size for fidelity (see scripts/quantize_gguf.py).

Usage (Ollama, direct — recommended)

No Modelfile needed. This repo ships Ollama template (phi family), system (kitten persona), and params files, so the HF integration picks them up automatically:

ollama run hf.co/KittyLM/kittylm-phi-4-mini-gguf:Q4_K_M
# other quants (when present): :Q8_0, :Q6_K, :Q5_K_S

Usage (Ollama, classic Modelfile)

A ready-made Modelfile lives in this repo (FROM points at the Q4_K_M file):

hf download KittyLM/kittylm-phi-4-mini-gguf --include "*.gguf" --local-dir ./gguf
hf download KittyLM/kittylm-phi-4-mini-gguf Modelfile --local-dir ./gguf
ollama create kittylm-phi-4-mini -f ./gguf/Modelfile
ollama run kittylm-phi-4-mini "Good night!"

Usage (llama.cpp / LM Studio)

Point llama.cpp (llama-cli -m <file>.gguf) or LM Studio at the .gguf file directly. Apply the model's chat template and keep the KittyLM system prompt (also shipped as the system file in this repo and as system_prompt.txt in KittyLM/kittylm-data).