Path	Run	Epochs	Adapter
`scratch-nft/checkpoint-180/`	scratch DiffusionNFT, job `219145`	200 (last save is 180)	EMA stored in `lora/` (legacy save)
`scratch-nft-or/checkpoint-180/`	scratch NFT-OR `or_mix`, job `219585`	180	EMA (`lora_ema/`)
`scratch-nft-or/checkpoint-200/`	same run	200	EMA (`lora_ema/`)

The NFT 200-epoch job only checkpointed at epoch starts (save_freq=20), so its last file is checkpoint-180, not 200.

Training recipe (both): Pick-a-Pic, PickScore+CLIP+HPSv2, 512², 40 sample steps, β=0.1, 4×A800, seed 42.

DrawBench (1024², 40 steps, EMA)

Checkpoint	ImageReward	CLIP	Aesthetic	PickScore	HPSv2	avg
scratch-nft ckpt-180	1.194	0.280	5.888	0.895	0.316	8.573
scratch-nft-or ckpt-180	1.292	0.285	5.938	0.897	0.321	8.733
scratch-nft-or ckpt-200	1.306	0.286	5.951	0.896	0.319	8.757

The NFT-OR run used collinear implicit_positive OR (α=0.05), which saturates after epoch 0. Do not treat the score gap as causal evidence that OR is active.

Load

python

from diffusers import StableDiffusion3Pipeline
import torch

pipe = StableDiffusion3Pipeline.from_pretrained(
    "stabilityai/stable-diffusion-3.5-medium",
    torch_dtype=torch.bfloat16,
)
pipe.load_lora_weights("HaC-RL/NFT-OR", subfolder="scratch-nft-or/checkpoint-200")

For the matched DrawBench row, use subfolder="scratch-nft/checkpoint-180" or scratch-nft-or/checkpoint-180.