Instructions to use HattoriHanzo1/Leonidas-4B-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 HattoriHanzo1/Leonidas-4B-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 HattoriHanzo1/Leonidas-4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf HattoriHanzo1/Leonidas-4B-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 HattoriHanzo1/Leonidas-4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf HattoriHanzo1/Leonidas-4B-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 HattoriHanzo1/Leonidas-4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf HattoriHanzo1/Leonidas-4B-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 HattoriHanzo1/Leonidas-4B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf HattoriHanzo1/Leonidas-4B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/HattoriHanzo1/Leonidas-4B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use HattoriHanzo1/Leonidas-4B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "HattoriHanzo1/Leonidas-4B-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": "HattoriHanzo1/Leonidas-4B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/HattoriHanzo1/Leonidas-4B-GGUF:Q4_K_M

Ollama
How to use HattoriHanzo1/Leonidas-4B-GGUF with Ollama:
```
ollama run hf.co/HattoriHanzo1/Leonidas-4B-GGUF:Q4_K_M
```
Unsloth Desktop

How to use HattoriHanzo1/Leonidas-4B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf HattoriHanzo1/Leonidas-4B-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": "HattoriHanzo1/Leonidas-4B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use HattoriHanzo1/Leonidas-4B-GGUF with Docker Model Runner:
```
docker model run hf.co/HattoriHanzo1/Leonidas-4B-GGUF:Q4_K_M
```

Lemonade

How to use HattoriHanzo1/Leonidas-4B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull HattoriHanzo1/Leonidas-4B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Leonidas-4B-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use HattoriHanzo1/Leonidas-4B-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 HattoriHanzo1/Leonidas-4B-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 HattoriHanzo1/Leonidas-4B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use HattoriHanzo1/Leonidas-4B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf HattoriHanzo1/Leonidas-4B-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 "HattoriHanzo1/Leonidas-4B-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"

Leonidas-4B

"Come and take them." — Leonidas I, 480 BC

Few parameters. No retreat.

Trenuje modele z pasji i dla społeczności. Jeśli moja praca ułatwia Ci życie lub oszczędza czas, każda postawiona kawa pomaga w opłaceniu kolejnych treningów GPU! ☕👇

Model Description

Leonidas-4B is a fine-tuned Polish reasoning model built on the Qwen3.5-4B hybrid architecture (Mamba + Attention). It was trained using LoRA fp16 on a curated 48k Polish Chain-of-Thought dataset, with native <think> reasoning blocks.

Forged by Hattori Hanzo — because an idiot admires complexity, a genius admires simplicity.

"An idiot admires complexity, a genius admires simplicity." — Terry A. Davis, TempleOS

Architecture

Property	Value
Base Model	Qwen3.5-4B (hybrid Mamba+Attention)
Parameters	~4B
Training Method	LoRA fp16 (r=16, alpha=16)
Trainable params	0.47%
Training Steps	1500
Final Loss	0.4389
Context Length	32768
Language	Polish 🇵🇱 + English

Training

Dataset: 48k Polish CoT (Chain-of-Thought) — mixed reasoning, math, logic, science
Format: ChatML with native <think> blocks
Platform: Kaggle T4 16GB
Phases:

Phase Steps LR Scheduler

1 2000 2e-4 linear

2 3000 5e-5 cosine

3 5000 3e-5 cosine

4 5000 1e-5 cosine

Phase	Steps	LR	Scheduler
1	2000	2e-4	linear
2	3000	5e-5	cosine
3	5000	3e-5	cosine
4	5000	1e-5	cosine

Available Files

File	Size	Description
`leonidas_f16.gguf`	8.41 GB	Full precision fp16
`leonidas_Q8_0.gguf`	4.47 GB	Q8_0 — best quality
`leonidas_Q6_K.gguf`	3.45 GB	Q6_K — great quality
`leonidas_Q4_K_M.gguf`	2.70 GB	Q4_K_M — recommended for most setups

Usage

llama.cpp

./llama-cli \
  -m leonidas_Q4_K_M.gguf \
  -p "Jesteś asystentem AI. Myśl krok po kroku." \
  --chat-template chatml \
  -n 1024

Ollama / OpenWebUI

Compatible with any OpenAI-compatible frontend supporting GGUF + ChatML template. ### Recommended Parameters `temperature: 0.6 top_p: 0.95 top_k: 40 repetition_penalty: 1.05`

Capabilities

✅ Native Polish reasoning with <think> CoT blocks
✅ Mathematics and logic
✅ Scientific explanations
✅ Sentiment analysis
✅ Code generation (Python, basics)
✅ Quantum physics concepts

Forge Stamp

general.author:   HattoriHanzo1
hanzo.base_model: Qwen3.5-4B
hanzo.leonidas:   Τότε ἐν τῇ σκιᾷ μαχούμεθα
                  ("Then we shall fight in the shade.")

License

Apache 2.0 — base model license from Qwen3.5-4B (Alibaba Cloud).

☕ Wsparcie Projektu

Stworzenie i dopracowanie tego modelu wymagało sporo czasu, testów i zasobów sprzętowych. Jeśli uznajesz go za użyteczny i chcesz wesprzeć dalszy rozwój otwartych projektów, możesz dorzucić swoją cegiełkę:

Dzieki za kazde wsparcie, widzimy sie przy kolejnych treningach! 🚀

Romani ite domum 😄 — Qapla'! ⚔️🖖

Downloads last month: 136

GGUF

Model size

4B params

Architecture

qwen35

Hardware compatibility

4-bit

6-bit

8-bit

16-bit

Model tree for HattoriHanzo1/Leonidas-4B-GGUF

Base model

Qwen/Qwen3.5-4B-Base

Finetuned

Qwen/Qwen3.5-4B

Adapter

(599)

this model

Collection including HattoriHanzo1/Leonidas-4B-GGUF

# Shinobi Tech 🥷⚡ *Precision-crafted open-source AI models,

Collection

10 items • Updated Jul 28

Leonidas-4B

Model Description

Architecture

Training

Available Files

Usage

llama.cpp

Ollama / OpenWebUI

Compatible with any OpenAI-compatible frontend supporting GGUF + ChatML template. ### Recommended Parameters temperature: 0.6 top_p: 0.95 top_k: 40 repetition_penalty: 1.05

Capabilities

Forge Stamp

License

Apache 2.0 — base model license from Qwen3.5-4B (Alibaba Cloud).

☕ Wsparcie Projektu

Model tree for HattoriHanzo1/Leonidas-4B-GGUF

Collection including HattoriHanzo1/Leonidas-4B-GGUF

Compatible with any OpenAI-compatible frontend supporting GGUF + ChatML template. ### Recommended Parameters `temperature: 0.6 top_p: 0.95 top_k: 40 repetition_penalty: 1.05`