Instructions to use rsshekhawat/Qwen-Edit-3DChibi-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rsshekhawat/Qwen-Edit-3DChibi-LoRA 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-2509", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("rsshekhawat/Qwen-Edit-3DChibi-LoRA") prompt = "Convert this image into 3D Chibi Style" 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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things

- Xet hash:
- 5e8bb8997279541b0ea544af2da14e01d2d0e4f8ac662872caff812429171131
- Size of remote file:
- 1.43 MB
- SHA256:
- badf550ed18a6fec4741732ec5c71858e57240f1c6845b7c5ef2dd19fe82c9fd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.