Text-to-Image
Diffusers
StableDiffusionXLPipeline
stablediffusionapi.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/xingguang with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/xingguang with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/xingguang", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 2e8b55b6d45605175766ea105d69e6b3ca9ab5dc1e2e3e9256cb92abe781ea03
- Size of remote file:
- 5.14 GB
- SHA256:
- 8ad8ed0a4dab7c7a1f312718cf593299010d538ee882310805fbd87ee2e2c02d
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