Instructions to use HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive",
	filename="Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-IQ3_M.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": [
				{
					"type": "text",
					"text": "Describe this image in one sentence."
				},
				{
					"type": "image_url",
					"image_url": {
						"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
					}
				}
			]
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M
# Run inference directly in the terminal:
llama-cli -hf HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M
# Run inference directly in the terminal:
llama-cli -hf HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_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 HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M
# Run inference directly in the terminal:
./llama-cli -hf HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_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 HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M

Use Docker

docker model run hf.co/HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M

LM Studio
Jan

vLLM

How to use HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M

Ollama
How to use HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive with Ollama:
```
ollama run hf.co/HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M
```

Unsloth Studio new

How to use HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive to start chatting

Pi new

How to use HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_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 HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M

Run Hermes

hermes

Docker Model Runner
How to use HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive with Docker Model Runner:
```
docker model run hf.co/HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M
```

Lemonade

How to use HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull HauhauCS/Gemma-4-E2B-Uncensored-HauhauCS-Aggressive:IQ3_M

Run and chat with the model

lemonade run user.Gemma-4-E2B-Uncensored-HauhauCS-Aggressive-IQ3_M

List all available models

lemonade list

[Request] GGUF version with MTP (Multi-Token Prediction) support

#10

by rggaini - opened 6 days ago

Discussion

rggaini

6 days ago

llama.cpp

now officially supports MTP

描述 (Description):

Hi author, thanks for the great model!

Since

(Multi-Token Prediction), could you please upload a GGUF version with MTP enabled?

Enabling MTP would significantly boost the inference speed (tokens/s) via speculative decoding. It would be very helpful for local deployment.

Thanks!

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment