Instructions to use google/gemma-2b-it-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use google/gemma-2b-it-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="google/gemma-2b-it-GGUF",
	filename="gemma-2b-it.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use google/gemma-2b-it-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf google/gemma-2b-it-GGUF
# Run inference directly in the terminal:
llama-cli -hf google/gemma-2b-it-GGUF

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf google/gemma-2b-it-GGUF
# Run inference directly in the terminal:
llama-cli -hf google/gemma-2b-it-GGUF

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 google/gemma-2b-it-GGUF
# Run inference directly in the terminal:
./llama-cli -hf google/gemma-2b-it-GGUF

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 google/gemma-2b-it-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf google/gemma-2b-it-GGUF

Use Docker

docker model run hf.co/google/gemma-2b-it-GGUF

LM Studio
Jan
Ollama
How to use google/gemma-2b-it-GGUF with Ollama:
```
ollama run hf.co/google/gemma-2b-it-GGUF
```

Unsloth Studio new

How to use google/gemma-2b-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 google/gemma-2b-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 google/gemma-2b-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 google/gemma-2b-it-GGUF to start chatting

Docker Model Runner
How to use google/gemma-2b-it-GGUF with Docker Model Runner:
```
docker model run hf.co/google/gemma-2b-it-GGUF
```

Lemonade

How to use google/gemma-2b-it-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull google/gemma-2b-it-GGUF

Run and chat with the model

lemonade run user.gemma-2b-it-GGUF-{{QUANT_TAG}}

List all available models

lemonade list

Is there any hope to make 500M and 1B parameters like apple OpenELM?

by yousef1727 - opened Feb 5, 2025

Discussion

yousef1727

Feb 5, 2025

I'm just wondering what if there is these sizes? that would be nice special on Android device

Some apps need tiny, mini or medium models for simple tasks not for QnA, i mean summarize, explain, text editing, etc

I so trust on google and I know maybe I'll see more models on future, Google Gemma is the only model who understands Arabic because Gemma Tokenizer split word not letters like gpt which mean he can understand meaning between words not letters, that reduce mistakes,

Finally I want to repeat Apple made big family of sizes why google don't?

Renu11

Google org May 3, 2025

Hi @yousef1727 , Great news! Based on your feedback, the Gemma team has released smaller Gemma 3 models, including the Gemma3-1b (both pretrained and instruction-tuned) specifically for text generation. We hope this meets your needs!

yousef1727

May 17, 2025

Thanks 👍 that can help me to continue my work with AI (Artificial Intelligence)

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