Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
modelslab.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/light-and-shadow-enhancem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/light-and-shadow-enhancem 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/light-and-shadow-enhancem", torch_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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 4b632c3469426274ac3569db823d6f19cdaca9858e3687ecf808a34e2e1ab3b7
- Size of remote file:
- 492 MB
- SHA256:
- d3408935036c60553f2e281be13a6a36cd3ea98507307e161f734caa36c14a31
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.