Instructions to use metercai/SimpleSDXL2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use metercai/SimpleSDXL2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("metercai/SimpleSDXL2", 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:
- ff7e9ebfd4ddc5c4c4718f282bef8aad158b02bbbaf39a7ba1a64eec94b99da1
- Size of remote file:
- 12 GB
- SHA256:
- d0f5464aba82d8c0f493c061d2aea78fce48c7629099ef7faf9b4305f4cff8af
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.