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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7fa1878b755045e83d46c736dac46417311db74165de9e66c21ff61a7f69a370
- Size of remote file:
- 3.44 GB
- SHA256:
- 6191b7f296fee949b4f3a6a2287c19074e23f9595007152aa2747e143d2cf1dd
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