Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Anime
Photorealistic
Sexy
stable-diffusion
stable-diffusion-diffusers
kazzear
Instructions to use Yntec/vividicAnime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/vividicAnime 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/vividicAnime", 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
Commit History
-
Adding `diffusers` weights of this model
This PR adds fp32 and fp16 weights in PyTorch and safetensors format to Yntec/vividicAnimecc574dd -
file
a42d118 -
Create README.md
2d2e698 -
Upload model_index.json
70391b7 -
Delete model_index.json
4b55f59 -
Delete safety_checker
36ff84d -
Adding `diffusers` weights of this model (#1)
- Adding `diffusers` weights of this model (8dbff12705b015de689b958d298e820fad0bcc9a)3c2845b -
file
5385039 -
initial commit
1e02925