Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
General
Anime
Art
Girl
Photorealistic
Realistic
Semi-Realistic
3D
zoidbb
XpucT
SG_161222
osi1880vr
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/DeliberateRealisticWoop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/DeliberateRealisticWoop with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/DeliberateRealisticWoop", 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:
- 2f0f74132e861b4bf9ebc335865be087e7562760e73c98266155bf694cd153aa
- Size of remote file:
- 2.38 GB
- SHA256:
- 1353ca11805d64a355402ac64fa5ee59a04148eb78617fc66eba8b57bcfb021c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.