Text-to-Image
Diffusers
StableDiffusionPipeline
stablediffusionapi.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/john-smith with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/john-smith with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/john-smith", 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
- Xet hash:
- 0ec41976c198d2426a739847a9bf01b7b2e0448a9a6f0f743bc8d8252c2badbe
- Size of remote file:
- 246 MB
- SHA256:
- fe98e35086a9b2ba0aef5af6aa177d0605374bfaf8b893ad9bb441962a0260f4
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