Instructions to use lvladikov/Krea2-Turbo-Distill-4step-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lvladikov/Krea2-Turbo-Distill-4step-LoRA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lvladikov/Krea2-Turbo-Distill-4step-LoRA") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
This reminds me of the SDXL-era DMD2
#4
by Goghor - opened
Very good LoRA, thank you very much!
funny you should say that :) DMD2 was one of the approaches I considered but after research for my 4 step lora and time and quality reasons I chose Progressive Distillation and LADD-style GAN critic instead.
If I ever find time and GPU resources a 2 step version of the lora could use DMD2 but also preliminary research shows that Progressive Distillation and LADD-style GAN critic might hold up well (and do faster training) at 2 step than DMD2.