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marcus-naslum/medieval_illumination_lora
medieval_illumination_lora is a machine learning model from marcus-naslum. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Style LoRA trained on a 17 medieval (European and Persian) illuminations. Compatible with SDXL base model found on Huggingface.
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Updated Aug 24, 2025
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From the Hugging Face model README
Style LoRA trained on a 17 medieval (European and Persian) illuminations. Compatible with SDXL base model found on Huggingface.
The keyword that must be given in the prompt is: "a medu"
To use with ComfyUI, you need to download and use a conversion script on the LoRA layer keys. Something like:
wget https://raw.githubusercontent.com/huggingface/diffusers/main/scripts/convert_diffusers_sdxl_lora_to_webui.py
python convert_diffusers_sdxl_lora_to_webui.py \
--input_lora data/medieval_LoRA/checkpoint-600/pytorch_lora_weights.safetensors \
--output_lora data/medieval_LoRA/medieval_comfyui.safetensors
To use with Diffusers, something like:
import torch
from diffusers import DiffusionPipeline, AutoencoderKL
vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
pipe = DiffusionPipeline.from_pretrained(
"/home/marcus-naslum/Documents/hf_models/sdxl-base-1.0",
vae=vae,
torch_dtype=torch.float16,
variant="fp16",
use_safetensors=True
)
pipe.load_lora_weights("data/medieval_LoRA/checkpoint-600")
_ = pipe.to("cuda")
prompt = "a medu of female beating priest, ferocious, colorful, snails" # @param
image = pipe(prompt=prompt, num_inference_steps=25).images[0]
image.resize((512, 512))