Instructions to use Omnico/Krea2_turbo_diff_loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Omnico/Krea2_turbo_diff_loras 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("Omnico/Krea2_turbo_diff_loras") prompt = "A photo-realistic photograph of a adult woman with long blonde hair, wearing a brown parka with a fur-lined hood. the woman, who appears to be in her late s or early twenties, has a serious expression and is resting her chin on her hand. she is looking directly at the camera with her blue eyes. her blonde hair is styled in loose waves and falls down her back. she is wearing a beige parka with a fur-lined hood, which is slightly open, revealing her bare shoulders. the parka has a zipper closure and two pockets on the front. the background is blurred, but it appears to be an outdoor setting with trees and a cloudy sky. the image has a sepia tone, giving it a melancholic atmosphere. the overall mood of the image is somber and contemplative.,," image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Thank you for the Krea2 diff LoRAs!
#2
by hotran0417 - opened
Thank you for making these Krea2 diff LoRAs!
I’ve been using them with the base model to replace some of my large checkpoints, and they’ve saved me a lot of storage space.
I’ve also been experimenting with extracting a few diff LoRAs myself with the help of AI, so I know this takes quite a bit of work. 😄 I only made a few before finding your repo.
Your work has been really useful to me. Thanks again, and keep it up! 👍
Thanks for your feedback. I'll publish my model conversion scripts on GitHub a little later when I'm confident they cover most cases.