Instructions to use diffusers/consistency-decoder-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/consistency-decoder-test with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/consistency-decoder-test", 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
- Xet hash:
- efb000688ea8fba2ac8d247d6e84fc6643c38c0de61b66de08a3af58d9643064
- Size of remote file:
- 2.93 MB
- SHA256:
- 414af7d7ebdba27aa0106f5f53eb5f317eefbbf759b89a0193e836f4a80e33bf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.