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:
- 91c894a774f41dc0b429dda43f7bd0e4215ac2c54093e8f6dd770e0385e73ece
- Size of remote file:
- 1.69 MB
- SHA256:
- 7db5ff7d3ecb978ff19e5fd4ac876df82ca7d0a9fd8c414451c19692a7757b00
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