Instructions to use xin0920/trained-sd3-saenewdata with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xin0920/trained-sd3-saenewdata with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xin0920/trained-sd3-saenewdata", 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:
- 289d300ae3939c40eb173e0781481ffafc3ae4cca7f0e2038e15acd872eeb932
- Size of remote file:
- 1.06 kB
- SHA256:
- ada6dae3fd76a7950f9e14393c14e707c741ab195ce65987f5695e590a7cd442
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