Instructions to use diffusers/lora-trained-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/lora-trained-xl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/stable-diffusion-xl-base-0.9", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("diffusers/lora-trained-xl") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download image_0.png from diffusers/lora-trained-xl: direct link, hf CLI and curl.
- Browser
- Download file 1.71 MB
-
https://huggingface.co/diffusers/lora-trained-xl/resolve/refs%2Fpr%2F1/image_0.png
- Command line
-
hf download hf://diffusers/lora-trained-xl@refs/pr/1/image_0.png
-
curl -L -o image_0.png https://huggingface.co/diffusers/lora-trained-xl/resolve/refs%2Fpr%2F1/image_0.png
1.71 MB

- Xet hash:
- 508933d905f593682b5c719eebaf69360b0781df8a633d116b94ea118aeaa011
- Size of remote file:
- 1.71 MB
- SHA256:
- 58d1b2931ae3f3f7f99c91f415c0a3021e93c14d4e54d496326eb7f1a40e12c6
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