Instructions to use fusing/ddpm-lsun-bedroom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fusing/ddpm-lsun-bedroom with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fusing/ddpm-lsun-bedroom", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2bb9786fc0b4d23cf97bdc779d269f995763721793c2e5d95a543ce77d1979fb
- Size of remote file:
- 455 MB
- SHA256:
- 23f0ba2284af43b85ced80d2af6338a9875dcf5ec97af93dfa97788fb6e41261
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.