Instructions to use apa224/scan42_unc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use apa224/scan42_unc with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("apa224/scan42_unc", 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-2000/optimizer.bin from apa224/scan42_unc: direct link, hf CLI and curl.
- Browser
- Download file 910 MB
-
https://huggingface.co/apa224/scan42_unc/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://apa224/scan42_unc/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/apa224/scan42_unc/resolve/main/checkpoint-2000/optimizer.bin
910 MB
- Xet hash:
- 96ed6f9b4f7bc765c94ac0606886190987f8ce4f4836527342f15a990037077d
- Size of remote file:
- 910 MB
- SHA256:
- b2bae777695d5d3849e45d8c688dbf3486c1f863f5196937af5b4500eb19f59a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.