Instructions to use fusing/ncsnpp-ffhq-ve-dummy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fusing/ncsnpp-ffhq-ve-dummy with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fusing/ncsnpp-ffhq-ve-dummy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download diffusion_model.pt from fusing/ncsnpp-ffhq-ve-dummy: direct link, hf CLI and curl.
- Browser
- Download file 7.23 MB
-
https://huggingface.co/fusing/ncsnpp-ffhq-ve-dummy/resolve/main/diffusion_model.pt
- Command line
-
hf download hf://fusing/ncsnpp-ffhq-ve-dummy/diffusion_model.pt
-
curl -L -o diffusion_model.pt https://huggingface.co/fusing/ncsnpp-ffhq-ve-dummy/resolve/main/diffusion_model.pt
7.23 MB
- Xet hash:
- 276ee35131961d2a2415140d0fde694ac6f00f79a90e1bd8b45f49bdcb5ff24c
- Size of remote file:
- 7.23 MB
- SHA256:
- 39602603c07d8f2770da739f717e529244287b7974d88d5ec2f65f4e19129018
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.