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
- Xet hash:
- 88aa74528eaac92d4622b74a4dfc1b65aae3cc9b9983762280ee4bffcf909605
- Size of remote file:
- 47.4 MB
- SHA256:
- 2a6983d2a2f17ef05db032fe9f6a6a67439e1dc284fbcc5143ff7cd0a00532f8
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