Instructions to use GraydientPlatformAPI/vivid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GraydientPlatformAPI/vivid with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("GraydientPlatformAPI/vivid", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ca3899a61748fda3a89af93306d41a4a23cee7aa787385908d061711755f8fda
- Size of remote file:
- 1.39 GB
- SHA256:
- 6f64d93f2e511f01deeba6958d59618567d82839cfbc6440166173e58f4e4300
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.