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:
- e0a936de94cd5d734179ff6936c1c0194b2d4b8b2e872e870240b1854d8ba10d
- Size of remote file:
- 23.7 MB
- SHA256:
- 59093aeacd4adc414bc45a931777d1f782255155c244536ef7d19aacfff5d682
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