0.4.0

What's Changed

• Fully revamped the training utils. Check out the Training 101 guide for a gentle start
• Added SDXL-Lightning. #305
• Added Latent Consistency Models and LCM-LoRA for Stable Diffusion XL. #297
• Added Style Aligned adapter to Stable Diffusion models. #289
• Added ControlLoRA (v2) adapter to Stable Diffusion XL. #285

Full Changelog: v0.3.1...v0.4.0

0.3.1

What's Changed

• Improved typing for Module and Chain (see #257 for details)
• Added missing PyPi classifiers to pyproject.toml e.g. Python versions

Full Changelog: v0.3.0...v0.3.1

0.3.0

What's Changed

• Initiated a full-fledged documentation website available at https://refine.rs
• Added a new SDLoraManager to easily load one or multiple community LoRA-s (e.g. CivitAI)
• Revamped entirely the LoRA adapter and added support for Conv2dLora
• Fixed various minor issues in solvers (fka schedulers)
• Added Euler's method to solvers
• Expanded IP-Adapter to support multiple image prompts
• Refactored IP-Adapter for better composability, e.g. with LoRA-s
• Added dense mask prompt support to Segment Anything
• Added DINOv2 to foundation models for high-performance visual features
• Added FreeU for improved quality at no cost
• Converted the test weights conversion script from bash to Python
• Replaced Poetry by Rye for Python dependencies management

New Contributors

• @brycedrennan
• @isamu-isozaki
• @israfelsr
• @piercus

Full Changelog: v0.2.0...v0.3.0

0.2.0

What's Changed

• Added Restart Sampling for improved image generation (example)
• Added Self-Attention Guidance to avoid e.g. too smooth images (example)
• Added T2I-Adapter for extra guidance (example)
• Added MultiDiffusion for e.g. panorama images
• Added IP-Adapter, aka image prompt (example)
• Added Segment Anything to foundation models
• Added Stable Diffusion XL 1.0 to foundation models
• Made possible to add new concepts to the CLIP text encoder, e.g. via Textual Inversion

Full Changelog: v0.1.0...v0.2.0

0.1.0

Initial release:

• Initiated core APIs (aka Fluxion), in particular: Chain , Context and Adapter
• Foundation model: Stable Diffusion 1.5
• Adapters: ControlNet, LoRA, Reference-Only Control
• Optional training utils
• Scripts for converting model weights into the Refiners format