Error Detection with unexpected labels: [CLS]and[SEP]

[littlecay]

I use offlinemode, and
config_file = 'D:/deeplearning/Grounded-Segment-Anything-main/GroundingDINO/groundingdino/config/GroundingDINO_SwinT_OGC.py' # change the path of the model config file
checkpoint_path = 'D:/deeplearning/Grounded-Segment-Anything-main/bert-base-uncased/groundingdino_swint_ogc.pth' # change the path of the model
image_path = 'D:/deeplearning/Grounded-Segment-Anything-main/1.jpg'
text_prompt = 'chair'
output_dir = 'D:/deeplearning/Grounded-Segment-Anything-main/output'
like this, in inference_on_a_image.py. However, the output results seems random. New labels like [CLS][SEP] apprear.
出现了很多的乱码标签[CLS][SEP]经查似乎与bert有关，且每次结果都是随机的

Anyone have any ideas? Thanks