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SD1.5 Direct Preference Optimization - DPO

28
330
2
Updated: Dec 23, 2023
base modelbasemodeldpo
Verified:
SafeTensor
Type
Checkpoint Trained
Stats
330
Reviews
Uploaded
Dec 22, 2023
Base Model
SD 1.5
Training
Steps: 2,000
Usage Tips
Clip Skip: 1
Hash
AutoV2
D294A157D5
0
0
0
0

Not my model, from the huggingface repo. This is an excellent merge model, particularly in the middle blocks. Try it yourself - take your favorite model, and block merge this at about 10% input, and 20% middle, and adjust from there.

Original U-Net: https://huggingface.co/mhdang/dpo-sd1.5-text2image-v1

bdsqlz's release: https://huggingface.co/bdsqlsz/dpo-sd-text2image-v1-fp16

bdsqlz released the sdxl model here: https://civitai.com/models/237681/dpo-sdxl-fp16 but us poor 1.5 users were left in the dark ages.

I had to do some hacking to get the fp32 version, so you will have to bring your own VAE.

Diffusion Model Alignment Using Direct Preference Optimization

Direct Preference Optimization (DPO) for text-to-image diffusion models is a method to align diffusion models to text human preferences by directly optimizing on human comparison data. Please check paper at Diffusion Model Alignment Using Direct Preference Optimization.

SD1.5 model is fine-tuned from stable-diffusion-v1-5 on offline human preference data pickapic_v2.

SDXL model is fine-tuned from stable-diffusion-xl-base-1.0 on offline human preference data pickapic_v2.