Instructions to use ShadeEngine/ddpm-ema-kirby-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShadeEngine/ddpm-ema-kirby-256 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ShadeEngine/ddpm-ema-kirby-256", 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
Download checkpoint-3500/optimizer.bin from ShadeEngine/ddpm-ema-kirby-256: direct link, hf CLI and curl.
- Browser
- Download file 910 MB
-
https://huggingface.co/ShadeEngine/ddpm-ema-kirby-256/resolve/main/checkpoint-3500/optimizer.bin
- Command line
-
hf download hf://ShadeEngine/ddpm-ema-kirby-256/checkpoint-3500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/ShadeEngine/ddpm-ema-kirby-256/resolve/main/checkpoint-3500/optimizer.bin
910 MB
- Xet hash:
- 6f9386875300c37e6676516a60a91884f4ae11e7b223a00de4e58304eef79e99
- Size of remote file:
- 910 MB
- SHA256:
- 8f8b79c810ee7678c4a277f01ccd4c4f6bc0c33e58cf617b2a7f7fe5d9afd214
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