Instructions to use xFutureTechx/May_SDXL_SD15_2024_Checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xFutureTechx/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("xFutureTechx/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 Settings
- Draw Things
- DiffusionBee
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Download README.md from xFutureTechx/May_SDXL_SD15_2024_Checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 42 Bytes
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https://huggingface.co/xFutureTechx/May_SDXL_SD15_2024_Checkpoints/resolve/refs%2Fpr%2F21/README.md
- Command line
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hf download hf://xFutureTechx/May_SDXL_SD15_2024_Checkpoints@refs/pr/21/README.md
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curl -L -o README.md https://huggingface.co/xFutureTechx/May_SDXL_SD15_2024_Checkpoints/resolve/refs%2Fpr%2F21/README.md
42 Bytes
metadata
license: creativeml-openrail-m