Instructions to use Moonxc/lora-trained-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Moonxc/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("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Moonxc/lora-trained-xl") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 2b67bbe561b03b7ad12064542cb0d0747b3476d328aa15b64b19b87d3e6fce36
- Size of remote file:
- 1.25 MB
- SHA256:
- 85054bc96dbf129d19e1ae70a5040389dede73b44779d62d86cfd0383b2d8eca
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