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 Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.bin from stablediffusionapi/hades: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/stablediffusionapi/hades/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://stablediffusionapi/hades/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/stablediffusionapi/hades/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 3894a9771906dc8fb92b447d9c9c3feaefa023a0e662a6f4ba3cd5926e9726d6
- Size of remote file:
- 335 MB
- SHA256:
- 7abaa63d1d4ffa7b3d83e314510127da7d29cccf91160af21370e5c4ad4e4877
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