Gemma

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Gemma is an open-weight Large Language Model (LLM) library from Google DeepMind, based on Gemini research and technology. It provides a JAX library for implementing and fine-tuning LLMs.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is gemma?

Gemma is an open-weight Large Language Model (LLM) library developed by Google DeepMind, leveraging research and technology from the Gemini models. This repository offers the implementation of the gemma PyPI package, providing a JAX library for both using and fine-tuning Gemma models. It supports multi-turn, multi-modal conversations and offers various versions of Gemma. The library is designed to run on CPU, GPU, and TPU, with specific RAM recommendations for GPU usage (8GB+ for 2B checkpoint, 24GB+ for 7B checkpoint). Extensive documentation, Colabs, and tutorials are available for sampling, multi-modal fine-tuning, and LoRA.

Best used for

Ideal for AI researchers and developers who need to implement and fine-tune open-weight large language models, develop multi-modal AI applications, and conduct advanced LLM research. Especially valuable for those working with JAX and requiring flexible deployment across CPU, GPU, and TPU.

Common actions

implement large language models

fine-tune LLMs

develop AI applications

conduct LLM research

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Capabilities

Key features

Open-weight LLM library
JAX implementation
Multi-turn conversation
Multi-modal capabilities
Model fine-tuning
Supports CPU, GPU, TPU

Target Audience

professorwriter

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What are the system requirements for running Gemma?

Gemma can run on CPU, GPU, and TPU. For GPU usage, it is recommended to have at least 8GB of RAM for the 2B checkpoint and 24GB of RAM for the 7B checkpoint to ensure optimal performance.

How can I get started with using Gemma?

To begin using Gemma, you first need to install JAX for your preferred hardware (CPU, GPU, or TPU) by following the instructions on the JAX website. After that, you can install the Gemma PyPI package using `pip install gemma`.

Does Gemma support multi-modal interactions?

Yes, Gemma supports multi-modal conversations. The ChatSampler API allows for multi-turn interactions that can incorporate images, enabling rich and dynamic conversations with the model.

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Research & Education › Academic Research Content & Design › AI Writing Assistants

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