Gemma
Gemma is a family of open-weights Large Language Model (LLM) by Google DeepMind, based on Gemini research and technology.
This repository contains the implementation of the
gemma PyPI package. A
JAX library to use and fine-tune Gemma.
For examples and use cases, see our documentation. Please report issues and feedback in our GitHub.
Installation
-
Install JAX for CPU, GPU or TPU. Follow the instructions on the JAX website.
-
Run
pip install gemma
Examples
Here is a minimal example to have a multi-turn, multi-modal conversation with Gemma:
from gemma import gm
# Model and parameters (Gemma 4)
model = gm.nn.Gemma4_E4B()
params = gm.ckpts.load_params(gm.ckpts.CheckpointPath.GEMMA4_E4B_IT)
# Example of multi-turn conversation
sampler = gm.text.ChatSampler(
model=model,
params=params,
multi_turn=True,
)
prompt = """Which of the 2 images do you prefer ?
Image 1: <|image|>
Image 2: <|image|>
Write your answer as a poem."""
out0 = sampler.chat(prompt, images=[image1, image2])
out1 = sampler.chat('What about the other image ?')
The same ChatSampler API works with all Gemma versions (2, 3, 3n, 4).
Our documentation contains various Colabs and tutorials, including:
Additionally, our examples/ folder contain additional scripts to fine-tune and sample with Gemma.
Learn more about Gemma
- To use this library: Gemma documentation
- Technical reports for metrics and model capabilities:
- Other Gemma implementations and doc on the Gemma ecosystem
Downloading the models
To download the model weights. See our documentation.
System Requirements
Gemma can run on a CPU, GPU and TPU. For GPU, we recommend 8GB+ RAM on GPU for The 2B checkpoint and 24GB+ RAM on GPU are used for the 7B checkpoint.
Contributing
We welcome contributions! Please read our Contributing Guidelines before submitting a pull request.
This is not an official Google product.
2 maintainers
Release files for gemma 4.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| gemma-4.0.1.tar.gz | 161.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| gemma-4.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 406.4 kB
Release files / gemma-4.0.1.tar.gz
| Download URL | gemma-4.0.1.tar.gz |
|---|---|
| Size | 161.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
00899dd6e608af25fed64455369b8ce64aec64e15614dec16eda1ce5f3520d2c
|
|
BLAKE2b-256 checksum How to use checksums |
e99f82968b43ae08104742051e6a9bbfd4a19563295d07db4d6107f83fb4ab56
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.13
|
Release files / gemma-4.0.1-py3-none-any.whl
| Download URL | gemma-4.0.1-py3-none-any.whl |
|---|---|
| Size | 245.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
a3ac8836f63fbf7e8d0934c851fc44c1422638596d157937ba8179db6bfb3e76
|
|
BLAKE2b-256 checksum How to use checksums |
decb1579fcd77ab62db40290068418458bc9a5d046fad6837021a8afaeb38510
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.13
|
