google-deepmind/gemma

Health v2 · maintenance only

Adoption not part of the score

5796 stars · 1032 forks observed · 2026-10-15

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

The official JAX-based Python library from Google DeepMind for running, sampling from, and fine-tuning the Gemma family of open-weight large language models. It supports multi-turn and multi-modal chat, LoRA fine-tuning, and checkpoint loading across Gemma versions 2 through 4.

Use cases

• run gemma llm locally with jax
• fine-tune gemma model
• lora fine-tuning for gemma
• multi-turn chat with gemma
• multimodal image chat with gemma
• load gemma checkpoints in python

When to choose

• you want to use or fine-tune Gemma models in JAX on CPU, GPU, or TPU
• you need the official DeepMind implementation with multi-modal and multi-turn chat support
• you want LoRA-based parameter-efficient fine-tuning of Gemma

When to avoid

• you need PyTorch or transformers-based tooling instead of JAX
• you want to run other model families beyond Gemma
• you need a production serving stack rather than a research library

Facets

library · maturity active

llm-inference llm-training machine-learning chatbot large-language-models deep-learning artificial-intelligence python cloud jax open-weights fine-tuning lora multimodal google-deepmind gpu

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markdown · JSON · MCP: product_card(name="google-deepmind/gemma")