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:
- 0f1bfd1e470eb3dfc3a2b51e0cd13ac0c03c7be47d2d3f19677d567588c1296a
- Size of remote file:
- 6.94 GB
- SHA256:
- a4dc5508454c6e9fec950d281c106d27a771cb91a02da3d3ac3cd8a7e75d5094
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.