Instructions to use alarazin/lora-trained-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alarazin/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-0.9", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("alarazin/lora-trained-xl") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- f2abe5e45a0b6dbae1df4a950fa431fa285c9eb4865f1d077251d39c33796a11
- Size of remote file:
- 1.75 MB
- SHA256:
- 35fb60a401a358e1df62f79a1b1e17c126ad50bb4ff017023e9237636f1539e3
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