Instructions to use peteromallet/Qwen-Image-Edit-InStyle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use peteromallet/Qwen-Image-Edit-InStyle with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-Edit", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("peteromallet/Qwen-Image-Edit-InStyle") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Amazing job
#1
by Zelan - opened
I just wanted to express my pleasure with this LoRa, and I really hope you continue to work on it. It is truly magical!
I've no idea how this is done, but I would love to be able to capture more subtle information from the following:
- Low poly style
- Cartoonosh style,
- video games UI (this would be amazing). Buttons, Sectons, icons, currencies, widgets, etc
- Board game design, cards, dice pawns, tokens, boards, etc
Again, amazing job!!! thank you!
That's so nice of you to say @Zelan , I'll be training another with a lot more diverse samples fairly soon
peteromallet changed discussion status to closed