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:
- 3a4939fd6647e3d7b1f59bb759d4b30b8c13cd4f998493c9d46e3fa9e18a59d6
- Size of remote file:
- 65.6 kB
- SHA256:
- d7caedfb46780825895718c7c8e9ee077e675c935ddfcf272f1c01a4fc8ea72d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.