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:
- ea6ca480d855cb2505e1e70b8fdb9f26d750468246e47c53c21e1e46c1bcbb89
- Size of remote file:
- 335 MB
- SHA256:
- c88431b1859b935160982d7687a547d8e59b7625faddb4020b368f5d2f59b18e
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