Instructions to use kyledam/gaixinhyc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kyledam/gaixinhyc with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kyledam/gaixinhyc", 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
- Draw Things
- DiffusionBee
- Xet hash:
- ba08602fa9e3d15d64afda2990ae2b3313c62f61393cd00bf4a91a4b758a7804
- Size of remote file:
- 128 MB
- SHA256:
- dbf010772b46d65a2afb2222c72761535c3e314bcfab6ff2daa5b58acf3e25f5
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