Text-to-Image
Diffusers
English
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
image-to-image
Instructions to use rrustom/stable-architecture-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rrustom/stable-architecture-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rrustom/stable-architecture-diffusers", 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:
- 30c7d7bb7e84f846cee9ec1c94fad12d9aed59c953a86a1e2656088b4808f6dd
- Size of remote file:
- 3.44 GB
- SHA256:
- b27bc122276b9a59d059fae07bd7b9cd030fac3ddef33bf79a9a3e284b9b093b
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