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:
- f3e3f1eebf6e474b0d24c85860ad24cd35dba128ae45cab917f5243df03db8c9
- Size of remote file:
- 1.37 MB
- SHA256:
- dcfbba140c5a63fd9d524ec9862ad14ba39f7a5dd5d26f207261362e716f72eb
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