Instructions to use FrankCCCCC/ddpm-ema-10k_cfm-corr-500-ss0.005-ep100-ema-run0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FrankCCCCC/ddpm-ema-10k_cfm-corr-500-ss0.005-ep100-ema-run0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FrankCCCCC/ddpm-ema-10k_cfm-corr-500-ss0.005-ep100-ema-run0", 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 ckpt/data.ckpt from FrankCCCCC/ddpm-ema-10k_cfm-corr-500-ss0.005-ep100-ema-run0: direct link, hf CLI and curl.
- Browser
- Download file 1.24 kB
-
https://huggingface.co/FrankCCCCC/ddpm-ema-10k_cfm-corr-500-ss0.005-ep100-ema-run0/resolve/main/ckpt/data.ckpt
- Command line
-
hf download hf://FrankCCCCC/ddpm-ema-10k_cfm-corr-500-ss0.005-ep100-ema-run0/ckpt/data.ckpt
-
curl -L -o data.ckpt https://huggingface.co/FrankCCCCC/ddpm-ema-10k_cfm-corr-500-ss0.005-ep100-ema-run0/resolve/main/ckpt/data.ckpt
1.24 kB
- Xet hash:
- c12095365580fef4fe72589fad171dee66fc0ce153de5bb4f45006b14d302589
- Size of remote file:
- 1.24 kB
- SHA256:
- e471ac5cabb2aa25d83f897aec933a344505ded9e0d237a38272abc236296e9e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.