metadata

tags:
  - stable-diffusion-xl
  - stable-diffusion-xl-diffusers
  - text-to-image
  - diffusers
  - lora
  - template:sd-lora
widget:
  - text: Orthodox church in the style of African buildings of the 6th century
    output:
      url: image_0.png
  - text: Orthodox church in the style of African buildings of the 6th century
    output:
      url: image_1.png
  - text: Orthodox church in the style of African buildings of the 6th century
    output:
      url: image_2.png
  - text: Orthodox church in the style of African buildings of the 6th century
    output:
      url: image_3.png
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: Orthodox church
license: openrail++

SDXL LoRA DreamBooth - litvan/SDXL_finetuned_for_russian_churches

Prompt
Orthodox church in the style of African buildings of the 6th century

Model description

These are litvan/SDXL_finetuned_for_russian_churches LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.

The main purpose of the model: Generate Orthodox churches in different cultural and architectural codes of countries

The weights were trained using DreamBooth.

LoRA for the text encoder was enabled: False.

Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.

Dataset for finetuning: litvan/russian_churches_with_blip_captioning

For training were used: 3 GPU A100(80Gb)

Trigger words

You should use Orthodox church to trigger the image generation.

Download model

You can do this using the following lines of code:

from diffusers import DiffusionPipeline

pipeline = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0").cuda()
pipeline.load_lora_weights("litvan/SDXL_finetuned_for_russian_churches")

For using refiner

refiner = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-refiner-1.0",
    text_encoder_2=pipeline.text_encoder_2,
    vae=pipeline.vae,
    torch_dtype=torch.float32,
    use_safetensors=True,
).cuda()