Instructions to use udg/epcdif with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use udg/epcdif with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("udg/epcdif", 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 unet/diffusion_pytorch_model.bin from udg/epcdif: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/udg/epcdif/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://udg/epcdif/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/udg/epcdif/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- e2e0b69bb727cfe77fdf63f4d2548b8c5ed715545a60440fd61523680f3d71bf
- Size of remote file:
- 3.44 GB
- SHA256:
- cc304fbe1c303b01562afa115ce19d6c7d35fd03a1deac524c0c6e8e75b7d2de
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