Text-to-Image
Diffusers
StableDiffusionXLPipeline
modelslab.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/hades with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/hades 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/hades", 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:
- 47e8743765c80b12b6009a20d79839eb85632b9d8986b977055319a9554d484f
- Size of remote file:
- 2.78 GB
- SHA256:
- ce2854b9f906e0ee4a57473c2c41dda5dc958d730d4f71ab589324d0c98d642c
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