Instructions to use EnD-Diffusers/May_SDXL_SD15_2024_Checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EnD-Diffusers/May_SDXL_SD15_2024_Checkpoints with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EnD-Diffusers/May_SDXL_SD15_2024_Checkpoints", 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:
- 5d52b13eaa759cbdc60f60f3830e2c0bd71ca7195a9d1005153005a11437aa0d
- Size of remote file:
- 2.13 GB
- SHA256:
- c18168a2807ae048fef1ec654a7e1836791a9a3d1d4f7f3619f38853c7e565ac
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.