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
Download text_encoder/pytorch_model.bin from Yntec/vividicAnime: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/Yntec/vividicAnime/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Yntec/vividicAnime@refs/pr/2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Yntec/vividicAnime/resolve/refs%2Fpr%2F2/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 4c7fe8565217a82d08d145d798897105a924df9b87b40650577d0fecd65cd7e9
- Size of remote file:
- 492 MB
- SHA256:
- 5287ae1982b9be0945ad86f66ae0383487ff6028a2ed9197e7396649a1a30d4e
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