Instructions to use marcelittle/ddr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use marcelittle/ddr with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("marcelittle/ddr", 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-5000/optimizer.bin from marcelittle/ddr: direct link, hf CLI and curl.
- Browser
- Download file 910 MB
-
https://huggingface.co/marcelittle/ddr/resolve/main/checkpoint-5000/optimizer.bin
- Command line
-
hf download hf://marcelittle/ddr/checkpoint-5000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/marcelittle/ddr/resolve/main/checkpoint-5000/optimizer.bin
910 MB
- Xet hash:
- ed2b3e806c3aa0feb9f7893146ad90e9f94fda11722332e279f95c7256196011
- Size of remote file:
- 910 MB
- SHA256:
- d2e3584e3e038739765d0e10d6a00bb0aab0e9c9d02a78eb36550be4954b5eb4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.