Instructions to use XGGNet/lora-sdxl-dog with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use XGGNet/lora-sdxl-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-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("XGGNet/lora-sdxl-dog") prompt = "a sbu dog in a bucket" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 03539f0b3f5a6f25ddffc1463129924c1eaf62a223e1ab26343de1ce95bdde06
- Size of remote file:
- 1.57 MB
- SHA256:
- c07588f14bf2beaa0ee8db32f22fec6395e4a1d5d5d29d1fba233b31986caaa6
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