Instructions to use wassimm/SDXL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wassimm/SDXL with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wassimm/SDXL", dtype=torch.bfloat16, device_map="cuda") prompt = "A captivating, existing living room updated with French style, keeping all current structural elements. Add warm, golden hues, plush velvet sofas, ornate gilded mirrors, and a crystal chandelier that casts enchanting reflections on the polished parquet floor. Ensure no alterations to structural elements" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Downloads last month
- 3
Model tree for wassimm/SDXL
Base model
stabilityai/stable-diffusion-xl-base-1.0