Instructions to use bullhug/animevae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bullhug/animevae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("bullhug/animevae", 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
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Download README.md from bullhug/animevae: direct link, hf CLI and curl.
- Browser
- Download file 130 Bytes
-
https://huggingface.co/bullhug/animevae/resolve/main/README.md
- Command line
-
hf download hf://bullhug/animevae/README.md
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curl -L -o README.md https://huggingface.co/bullhug/animevae/resolve/main/README.md
130 Bytes
metadata
language:
- en
library_name: diffusers
tags:
- vae
Diffusers format of animevae.pt from https://huggingface.co/Elaina3/nai