Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
Base Model
Photorealistic
Anime
Art
Realistic
Semi-Realistic
SG161222
diffusionfanatic1173
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/VisionVision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/VisionVision 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/VisionVision", 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:
- 34e672600a31f712150e2efd5f7348a2d7ca185d0dc4a518dc6d0e1c376ec64b
- Size of remote file:
- 492 MB
- SHA256:
- 31597503653bebcc52f285772523f1303b0bb2f13375977eec4381e18e35cb9e
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