mattmireles/gemma-tuner-multimodal

Health v2 · maintenance only

Flags: young

Adoption not part of the score

1495 stars · 103 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python tool for LoRA fine-tuning of Gemma 4 and 3n models on text, images, and audio using Apple Silicon's Metal Performance Shaders. It supports streaming training data from GCS/BigQuery and includes a real-time browser-based training visualizer.

Use cases

• fine-tune gemma on mac without nvidia gpu
• train multimodal lora on images and audio
• fine-tune gemma 3n on apple silicon
• stream training data from bigquery
• create custom vision question answering model
• audio captioning fine-tuning

When to choose

• you have a Mac with Apple Silicon and no NVIDIA GPU
• you need multimodal (image/audio/text) LoRA fine-tuning of Gemma
• your training data lives in GCS or BigQuery and is too large for local disk

When to avoid

• you need to fine-tune models other than Gemma
• you rely on CUDA-specific tooling like Unsloth or axolotl
• you need production-scale distributed multi-GPU training

Facets

library · maturity active

llm-training machine-learning deep-learning machine-learning large-language-models deep-learning python lora fine-tuning apple-silicon mps multimodal gemma peft macos gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="mattmireles/gemma-tuner-multimodal")