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:
- 54d83d58c5011d65db02a9932584e1092280fc525b21e4e8214af9db3fe973a1
- Size of remote file:
- 1.55 MB
- SHA256:
- 851fc8ec61819b083ba533acd4d950d8263c027129e527f2e30c6606f4d57feb
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