Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Photorealistic
Base model
Abstract
Fusch
stable-diffusion
stable-diffusion-1.5
stable-diffusion-diffusers
Instructions to use Yntec/RealLife with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/RealLife 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/RealLife", 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
Commit History
-
Update README.md
Verified signaturea4feb8e -
Update README.md
Verified signature4352f72
-
Update README.md
4777280 -
Update README.md
62785d1 -
Update README.md
e0a6617 -
Update README.md
492249f -
Update README.md
cacd015 -
Create README.md
3a3ed2e -
Update model_index.json
f5fe5e2 -
Update scheduler/scheduler_config.json
1ec2960 -
Upload model_index.json
501941d -
Delete model_index.json
64d2e63 -
Cleanup
88592d7 -
Adding `diffusers` weights of this model (#1)
- Adding `diffusers` weights of this model (9d6832fd0e2d272d52c33f4e0130b3ac008ca186)c7dfcc9 -
file
fbba896 -
initial commit
72d1885