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:
- 3044fb479cdcb8673aa735e93d20311076a8da181d1d3fa111171a87a60464c5
- Size of remote file:
- 246 MB
- SHA256:
- 1f7f9191652a0a0fdc33cfe5e8bd002dfc0d26a4f2d4ca6d30415c4edf13b4d6
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