Instructions to use Jihyeon-2/lora-trained-xl_dog with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jihyeon-2/lora-trained-xl_dog with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Jihyeon-2/lora-trained-xl_dog") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- c1fb564b361581d96fa6ca68cd75743ea2d004f7202031819935c04f22cfd20b
- Size of remote file:
- 1.51 MB
- SHA256:
- 557eee005518d2ded8e5ef591b56e714ebbe9d6fef37a6645a6bf0a970a60ad7
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