Gemma Tuner Multimodal

Fine-tune Gemma 3n and 4 models on your Mac using text, images, and audio without needing an NVIDIA GPU. This runs entirely on Apple Silicon through Metal Performance Shaders and supports LoRA parameter-efficient training. The standout feature is streaming datasets from GCS or BigQuery so you can train on huge datasets without copying everything locally. You get a CLI with a wizard for setup, separate modes for instruction tuning versus completion, and proper multimodal support including audio transcription, which is rare for local Mac training. If you have domain-specific data and an M-series Mac, this gives you a complete fine-tuning pipeline that actually runs locally instead of just theoretically supporting it.

skills.sh installs: 537
GitHub stars: 61
last updated: Jul 14, 2026

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Install

$ npx -y skills add aradotso/trending-skills --skill gemma-tuner-multimodal --agent claude-code

Installs into .claude/skills of the current project.

Files

Gemma Multimodal Fine-Tuner

Skill by ara.so — Daily 2026 Skills collection.

Fine-tune Gemma 4 and Gemma 3n models on text, images, and audio data entirely on Apple Silicon (MPS), with support for streaming large datasets from GCS/BigQuery without filling local storage.

What It Does

Text LoRA: instruction-tuning or completion fine-tuning from local CSV
Image + Text LoRA: captioning and VQA from local CSV
Audio + Text LoRA: the only Apple-Silicon-native path for this modality
Cloud streaming: train on terabytes from GCS/BigQuery without local copy
MPS-native: no NVIDIA GPU required — runs on MacBook Pro/Air/Mac Studio

Installation

Prerequisites

macOS 12.3+ with Apple Silicon (arm64)
Python 3.10+ (native arm64, not Rosetta)
Hugging Face account with Gemma access

# Install Python 3.12 if needed
brew install python@3.12

# Create venv
python3.12 -m venv .venv
source .venv/bin/activate

# Verify arm64 (must show arm64, not x86_64)
python -c "import platform; print(platform.machine())"

# Install PyTorch
pip install torch torchaudio

SKILL.md on GitHub

Details

Repository: github.com/aradotso/trending-skills
First seen: Jun 3, 2026