Text-to-Image
Diffusers
StableDiffusionXLPipeline
stablediffusionapi.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/zhima-jp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/zhima-jp 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/zhima-jp", 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:
- 99e9b96fc1aadf3017bcbb5ae951b446b90823419f375890dfe55f8ba1c26c60
- Size of remote file:
- 5.14 GB
- SHA256:
- f621d914d0f7c4adc419ce88caa212a8a5e137c1ba94105e464808c54dfafa27
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