When you trained the de-distilled model did you use guidance > 1?

--save_model_as="safetensors" \
--full_bf16 \
--output_name="momo_sdxl_dreambooth" \
--lr_scheduler_num_cycles=8 \
--max_data_loader_n_workers=0 \
--learning_rate=1e-04 \
--lr_scheduler="constant" \
--train_batch_size=1 \
--max_train_steps=10000 \
--save_every_n_steps=500 \
--mixed_precision="bf16" \
--save_precision="bf16" \
--cache_latents \
--cache_latents_to_disk  \
--optimizer_type="Adafactor" \
--optimizer_args \
--bucket_reso_steps=64 \
--noise_offset=0.0 \
--gradient_checkpointing \
--bucket_no_upscale \
--train_text_encoder \
--sample_every_n_epochs=1 \
--sample_every_n_steps=500 \
--sample_sampler="euler" \

--save_model_as="safetensors" \
--full_bf16 \
--output_name="momo_sdxl_dreambooth" \
--lr_scheduler_num_cycles=8 \
--max_data_loader_n_workers=0 \
--learning_rate=1e-04 \
--lr_scheduler="constant" \
--train_batch_size=1 \
--max_train_steps=10000 \
--save_every_n_steps=500 \
--mixed_precision="bf16" \
--save_precision="bf16" \
--cache_latents \
--cache_latents_to_disk  \
--optimizer_type="Adafactor" \
--optimizer_args \
--bucket_reso_steps=64 \
--noise_offset=0.0 \
--gradient_checkpointing \
--bucket_no_upscale \
--train_text_encoder \
--sample_every_n_epochs=1 \
--sample_every_n_steps=500 \
--sample_sampler="euler" \