ddpo-alignment

This model was finetuned from Stable Diffusion v1-4 using DDPO and a reward function that uses LLaVA to measure prompt-image alignment. See the project website for more details.

The model was finetuned for 200 iterations with a batch size of 256 samples per iteration. During finetuning, we used prompts of the form: "a(n) <animal> <activity>". We selected the animal and activity from the following lists, so try those for the best results. However, we also observed limited generalization to other prompts.

Activities:

• washing dishes
• playing chess
• riding a bike

Animals:

• cat
• dog
• horse
• monkey
• rabbit
• zebra
• spider
• bird
• sheep
• deer
• cow
• goat
• lion
• tiger
• bear
• raccoon
• fox
• wolf
• lizard
• beetle
• ant
• butterfly
• fish
• shark
• whale
• dolphin
• squirrel
• mouse
• rat
• snake
• turtle
• frog
• chicken
• duck
• goose
• bee
• pig
• turkey
• fly
• llama
• camel
• bat
• gorilla
• hedgehog
• kangaroo