Size mismatch for gpt_model.load_state_dict(model_weight, strict=False)

I use "python autoregressive/sample/sample_t2i.py
--vq-ckpt /data/checkpoints/vq/vq_ds16_t2i.pt
--gpt-ckpt /data/checkpoints/t2i/ControlAR/canny_MR.safetensors
--gpt-model GPT-XL --image-size 512
--condition-type seg --seed 0 --condition-path condition/example/t2i/multigen/bird.jpg
--prompt 'A bird made of blue crystal'
--adapter-size small
--control-strength 0.6"

But it report:"File "ControlAR-main/autoregressive/sample/sample_t2i.py", line 68, in main
gpt_model.load_state_dict(model_weight, strict=False)
File "/root/miniconda3/envs/varsr/lib/python3.9/site-packages/torch/nn/modules/module.py", line 2153, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for Transformer:
size mismatch for condition_mlp.uncond_embedding: copying a param with shape torch.Size([2304, 1280]) from checkpoint, the shape in current model is torch.Size([1024, 1280]). "

It seems that the weight is not correct when "/canny_MR.safetensors" weight is loaded, can you help me solve it?

Start at autoregressive/sample/sample_t2i.py line 68 and reproduce the provided command with the GPT-XL setting and canny_MR.safetensors checkpoint. Compare the model configuration with the checkpoint's condition_mlp.uncond_embedding shape. Done means the checkpoint loads without the reported mismatch and the sample command proceeds successfully.