Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
Photorealistic
Realistic
Semi-Realistic
Art
Render
Lineart
WarAnakin
RunDiffusion
SG_161222
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/CrystalReality with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/CrystalReality 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/CrystalReality", 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:
- 4531f0a643ec131d2d5658a7dc9cdbe30cce66976454198c4462456f72321c89
- Size of remote file:
- 492 MB
- SHA256:
- 64d3bd58c652a7ce7ca8cf505b3da487d4145bc7d6b827026dec0d29f7d82982
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.