In-depth articles, guides, and analysis to help you master on-device AI.
An advanced tutorial on fine-tuning Gemma 3n models using the Unsloth library for maximum performance and memory efficiency. Learn how to adapt Gemma 3n to specific tasks on consumer hardware.
Explore Gemma 3n's powerful vision capabilities. Learn how to use Gemma 3n to describe images, answer questions about them (VQA), and perform basic OCR, complete with Python code examples.
Learn how to use Gemma 3n's native multimodal capabilities to transcribe audio files into text. This tutorial covers the setup and provides a Python code example using the `mlx-vlm` library.
A step-by-step guide to setting up and running Google's Gemma 3n models locally using Ollama. Cover installation, model pulling, and basic interactions on all major operating systems.
A creative tutorial on how to use Gemma 3n's code generation capabilities to create and manipulate Scalable Vector Graphics (SVGs) directly from text prompts.
A practical guide to understanding the differences between Gemma 3n's E2B and E4B models. Learn which version offers the best balance of performance and efficiency for your hardware.
A deep-dive comparison between Google's Gemma 3n and Meta's Llama 3 for local development. We analyze benchmarks, hardware needs, and use cases to help you choose.
A step-by-step guide to adapting the powerful Gemma 3n model for your specific needs using Low-Rank Adaptation (LoRA), one of the most efficient fine-tuning techniques.
Get started with Google's latest open-source model, Gemma 3n. This step-by-step tutorial walks you through setting it up on your local machine.
A beginner-friendly visual guide to running Google's Gemma 3n models on your local computer using LM Studio. No command line needed!