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
- Draw Things
- DiffusionBee
- Xet hash:
- 6fe2e8f46689750b11b7a67ceffecbd25a0fe764ad89fdc50f3d6dc68d90f499
- Size of remote file:
- 492 MB
- SHA256:
- c08401b44c95587c31f334b689599621b80968c6a6c74aa8f69716e036267299
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.