Instructions to use fusing/ddpm-celeba-hq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fusing/ddpm-celeba-hq with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fusing/ddpm-celeba-hq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08c624e6dd974cdc6dabbb7e3810a66fe10a8e955cb302d7b6f6f51c7a857042
- Size of remote file:
- 455 MB
- SHA256:
- b752ba96bcbbf21db1bee1d1bc3d1bb6db541d71fdd303e2a4a127ec0ea5abef
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.