Fine-Tuned Qwen-Image-Edit vs Nano-Banana: Generating 1.2 Million Images

Links + Notes 📝 https://www.oxen.ai/blog Join Fine-Tune Fridays 🔧 https://oxen.ai/community Discord 🗿 https://discord.com/invite/s3tBEn7Ptg Use Oxen AI 🐂 https://oxen.ai/ Oxen.ai offers one click fine-tuning or fine-tunes for you! Built on top of the worlds best data versioning tool, we offer tools to automate model evals, generate synthetic data, and effortlessly fine-tune models. -- Chapters 0:00 Using Qwen-Image-Edit to generate 1.2 million images and cutting inference costs 5:45 The Task: Generating tables and workbenches in different colors 7:30 Testing Nano-Banana first to see if we even need to fine-tune 13:30 The Pricing Dilemma 16:26 Question: How did we evaluate the generated table quality 17:15 Question: How did we pass in the colors we wanted 18:48 How we kicked off the fine-tuning from the dataset 21:31 How Baseten provisions the GPUs to kick off a training job 24:44 What you see while fine-tuning 26:22 The inference optimizations 37:10 Using a Lighting LoRA speed up inference by reducing inference steps 39:26 General Questions