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
Commit History
-
Prep for Final LoRA release
Verified signatureeb72999 -
Prep for Final LoRA release
Verified signature6c4d38a
-
Update assets in relation to 60K checkpoint release
Verified signature6237446
-
Assets update in prep for 42K checkpoint release
Verified signature4cd5b40
-
Assets for 26K Checkpoint
Verified signature6a5a5bc
-
Checkpoint 14K which removes 44% of the prediction error a plain 4-step run has against the 8-step teacher
Verified signature8356e5f
-
chk10000
Verified signature84c91cc -
update latest to chk6000 which has improved over chk5000
Verified signature5037d2b
-
Work in progress, with already good quality checkpoint 5000, comfyui model and info, full documentation and preview assets
Verified signatureccda50a