Instructions to use kiltaiga/pepe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kiltaiga/pepe with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kiltaiga/pepe", 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 vae/diffusion_pytorch_model.bin from kiltaiga/pepe: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/kiltaiga/pepe/resolve/refs%2Fpr%2F1/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://kiltaiga/pepe@refs/pr/1/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/kiltaiga/pepe/resolve/refs%2Fpr%2F1/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 10c478b9a3f535ef106c517bb29beed4da01290440bf1561c65aba85accd9afd
- Size of remote file:
- 335 MB
- SHA256:
- e63a9e25de3dac34d784011fa21e21447d123b6cc3b0c48bd8f3514c479a67c5
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