Open-Source Image Generation: Diffusion Models & LoRA - AI Build & Learn

​Welcome to AI Build & Learn, a weekly AI engineering stream where we pick a new topic and learn by building together.

​This event is about generating images with AI. There's no single model we're locked into, the point is to explore what's out there and actually try a few. We'll focus on open-source models, but you're welcome to bring commercial ones (DALL·E, Midjourney, and friends) if you want to compare.

​We'll try to look at both major families: diffusion-based models (the dominant approach today) and transformer-based / autoregressive image models. I'll research and try some of the best open-source options ahead of the stream, and if time allows we'll also try fine-tuning with LoRA to teach a model a new style or subject.

​Some things to look up to get started:

​Open-source models:

• ​FLUX.2 (Black Forest Labs): current open-weight quality benchmark; DiT backbone, up to 4MP, multi-image reference

• ​Stable Diffusion 3.5 / SDXL (Stability AI): deepest ecosystem — LoRA, ControlNet, inpainting, countless fine-tunes

• ​Qwen-Image (Alibaba): strong all-rounder, especially good at rendering text (including Chinese)

• ​Z-Image / Z-Image-Turbo: Apache-2.0, near FLUX.2 quality in just a few steps (fast and commercial-friendly)

• ​HunyuanImage (Tencent): another high-quality open-weight option

​Tooling:

• ​Hugging Face Diffusers: https://github.com/huggingface/diffusers

• ​ComfyUI: node-based workflows: https://github.com/comfyanonymous/ComfyUI

• ​LoRA fine-tuning for diffusion models

​Reources

• ​GitHub: https://github.com/sagecodes/ai-build-and-learn

• ​Events Calendar: https://luma.com/ai-builders-and-learners

• ​Slack (Discuss during the week): Flyte Slack Group

• ​Hosted by Sage Elliott: https://www.linkedin.com/in/sageelliott/

​In this stream

• ​Intro to topic

• ​Community Discussion

• ​Practical examples

​Community challenge (optional)

​Try spending 30–90 minutes during the week learning or building something related to the topic, then share what you’re working on in Slack.

​Note on Flyte / Union

​You may see Flyte used in some demos. Flyte is an open-source AI orchestration platform maintained by Union (where I work) for building scalable, durable, and observable AI workflows. You do not need to use Flyte to participate.

• ​Union: https://www.union.ai/

• ​Flyte: https://flyte.org/

​Drop a comment with ideas for future topics (agents, RAG, MLOps, robotics, frameworks, and more).