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:
- 1a9d5279a19e2b472370ea56a84297f5ae0a371b7727f6ac91635a11408520cd
- Size of remote file:
- 1.55 MB
- SHA256:
- e03cdef1432c1e321292b9519cefce3a8673199c4446729f63001a62de342e63
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.