Fast LoRA inference for Flux with Diffusers and PEFT
What changed
In this post, we take the Flux.1-Dev model for text-to-image generation because of its widespread popularity and adoption, and how to optimize its inference speed when using LoRAs (~2.3x). It has over 30k adapters trained with it (as reported on the Hugging Face Hub platform). Therefore, its importance to the community is significant.
Why it matters
A concrete addition to Practical AI: Tools, Models & Frameworks: it changes what's available to builders today rather than being general commentary.
How it compares
Related prior coverage to compare against:
- (LoRA) Fine-Tuning FLUX.1-dev on Consumer Hardware
- Parameter-Efficient Fine-Tuning using 🤗 PEFT
- Bringing Nunchaku 4-bit Diffusion Inference to Diffusers
Sources
- Fast LoRA inference for Flux with Diffusers and PEFT (huggingface-blog)primary