Instructions to use ostris/sdxl-sd1-vae-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ostris/sdxl-sd1-vae-lora 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("ostris/sdxl-sd1-vae-lora") prompt = "photo in the sd1 latent space" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
SDXL SD1/2 VAE LoRA
This LoRA converts SDXL models to use the SD1/2 latent space. More info coming soon.
I recommend using this VAE with this LoRA sd-vae-ft-mse-original
Examples
Coming Soon
How to Use
Coming soon
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Model tree for ostris/sdxl-sd1-vae-lora
Base model
stabilityai/stable-diffusion-xl-base-1.0