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
Download assets/portrait_compare_turbo.jpg from lvladikov/Krea2-Turbo-Distill-4step-LoRA: direct link, hf CLI and curl.
- Browser
- Download file 622 kB
-
https://huggingface.co/lvladikov/Krea2-Turbo-Distill-4step-LoRA/resolve/main/assets/portrait_compare_turbo.jpg
- Command line
-
hf download hf://lvladikov/Krea2-Turbo-Distill-4step-LoRA/assets/portrait_compare_turbo.jpg
-
curl -L -o portrait_compare_turbo.jpg https://huggingface.co/lvladikov/Krea2-Turbo-Distill-4step-LoRA/resolve/main/assets/portrait_compare_turbo.jpg
622 kB

- Xet hash:
- 598268e860c33c434d1efa285a9b9df68e40655b5ce793b19c80b4f9e16cd831
- Size of remote file:
- 622 kB
- SHA256:
- 38055a587da2eff83aca541ca347baa995475a196f09fd7e68e974f750f055b5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.