Instructions to use ggml-org/gemma-3n-E4B-it-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ggml-org/gemma-3n-E4B-it-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="ggml-org/gemma-3n-E4B-it-GGUF",
	filename="gemma-3n-E4B-it-Q8_0.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use ggml-org/gemma-3n-E4B-it-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 ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf ggml-org/gemma-3n-E4B-it-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf ggml-org/gemma-3n-E4B-it-GGUF:Q8_0

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 ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf ggml-org/gemma-3n-E4B-it-GGUF:Q8_0

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 ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ggml-org/gemma-3n-E4B-it-GGUF:Q8_0

Use Docker

docker model run hf.co/ggml-org/gemma-3n-E4B-it-GGUF:Q8_0

LM Studio
Jan
Ollama
How to use ggml-org/gemma-3n-E4B-it-GGUF with Ollama:
```
ollama run hf.co/ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
```

Unsloth Studio

How to use ggml-org/gemma-3n-E4B-it-GGUF 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 ggml-org/gemma-3n-E4B-it-GGUF 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 ggml-org/gemma-3n-E4B-it-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ggml-org/gemma-3n-E4B-it-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use ggml-org/gemma-3n-E4B-it-GGUF with Docker Model Runner:
```
docker model run hf.co/ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
```

Lemonade

How to use ggml-org/gemma-3n-E4B-it-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ggml-org/gemma-3n-E4B-it-GGUF:Q8_0

Run and chat with the model

lemonade run user.gemma-3n-E4B-it-GGUF-Q8_0

List all available models

lemonade list

gemma-3n-E4B-it-GGUF

File size: 1,156 Bytes

---
license: gemma
library_name: gguf
base_model: google/gemma-3n-e4b-it
---

> [!Note]
> This version does not contain multimodal support. We are still working on adding multimodal.

# Gemma 3n model card

**Original model**: https://huggingface.co/google/gemma-3n-E4B-it

**Model Page**: [Gemma 3n](https://ai.google.dev/gemma/docs/gemma-3n)

**Resources and Technical Documentation**:

-   [Responsible Generative AI Toolkit](https://ai.google.dev/responsible)
-   [Gemma on Kaggle](https://www.kaggle.com/models/google/gemma-3n)
-   [Gemma on HuggingFace](https://huggingface.co/collections/google/gemma-3n-685065323f5984ef315c93f4)
-   [Gemma on Vertex Model Garden](https://console.cloud.google.com/vertex-ai/publishers/google/model-garden/gemma3n)

**Terms of Use**: [Terms](https://ai.google.dev/gemma/terms)\
**Authors**: Google DeepMind

## Example usage

### With llama.cpp

To install llama.cpp on your system, see [installation guide](https://github.com/ggml-org/llama.cpp/blob/master/README.md)

```sh
llama-cli -m ggml-org/gemma-3n-E4B-it-GGUF:Q8_0
```

### With LM Studio

Search for `gemma-3n-E4B-it-GGUF` and add it to your model library