Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Photorealistic
Food
Cars
Oragani
stable-diffusion
stable-diffusion-1.5
stable-diffusion-diffusers
Instructions to use Yntec/ReaDiff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/ReaDiff 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/ReaDiff", 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:
- a469dacb1cc455dceb00517f8e6b6dccb03ff1564b1e6cdd3f316b3dcdd10b5e
- Size of remote file:
- 492 MB
- SHA256:
- e2c364b4d99ceef6291ac967e010961a7da8728e56ff034b11ff58a65b38d98a
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