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ldm-lsun-church
pearisli/ldm-lsun-church
ldm-lsun-church is a unconditional image generation model from pearisli. Use it for the unconditional image generation task on the model card, and read the license before you ship it in a product. It is set up for diffusers. The card lists the license as mit.
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At a glance
- Task
- Unconditional Image Generation
- Library
- diffusers
- License
- mit
- Access
- Public
- Created
- Oct 2, 2025
- Updated
- Oct 2, 2025
- SHA
- f58c4ed2
Datasets
Model card
From the Hugging Face model README
Latent Diffusion Models (LDM)
Model Details
Model Description
The model was resumed for 150,000 steps starting from the LDM-KL-8 checkpoint to incorporate the attention mechanism as implemented in diffusers, which differs from the original version. It leverages the autoencoder from stable-diffusion-2-base and achieves the FID-50K score of 4.63.
Note: To use this model with diffusers, replace the file diffusers/models/unets/unet_2d.py with the unet_2d.py provided in this repository.
Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->Inference with a pipeline
from diffusers import LDMPipeline
model_id = "pearisli/ldm-lsun-church"
# load model and scheduler
pipeline = LDMPipeline.from_pretrained(model_id)
# run pipeline in inference (sample random noise and denoise)
image = pipeline(num_inference_steps=200).images[0]
# save image
image.save("ldm_generated_image.png")
- Task
- Unconditional Image Generation
- Library
- diffusers
- License
- mit
- Languages
- en
- Created
- Oct 2, 2025
- Updated
- Oct 2, 2025