Text-to-Image
Diffusers
StableDiffusionXLPipeline
modelslab.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/xingbie with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/xingbie 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/xingbie", dtype=torch.bfloat16, device_map="cuda") prompt = "a girl wandering through the forest" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 4bb483b9e529ac2e99e932b1d786a79a3fc1a5710b390169cb214b79a6008a97
- Size of remote file:
- 246 MB
- SHA256:
- 83ca4990134cc2d58a4ca903d81a6b867b83f2f20f7f1c78b99e4e8e3b87ac2c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.