Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
Photorealism
anime
art
artistic
darkstorm2150
stable-diffusion
stable-diffusion-1.5
stable-diffusion-diffusers
Instructions to use Yntec/Prodigy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Prodigy 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/Prodigy", 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:
- 6c78c9dce04a2436bfdfc13252db33ec5b1875a667e9d669f4b70466061321e8
- Size of remote file:
- 246 MB
- SHA256:
- 2b01b0032c03ece16b7715e9cf15c9fb6224ee11747847e3d575a7bd28e14130
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.