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
- Draw Things
- DiffusionBee

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