RuntimeError: Error(s) in loading state_dict for Blip2OPT: size mismatch for opt_proj.weight: copying a param with shape torch.Size([2560, 768]) from checkpoint, the shape in current model is torch.Size([768, 768]). size mismatch for opt_proj.bias: copying a param with shape torch.Size([2560]) from checkpoint, the shape in current model is torch.Size([768]).

[chilljudaoren]

load typr: model = load_model("blip2_opt", "caption_coco_opt2.7b", is_eval=True, device=device)

Traceback (most recent call last):

File "/home/czh/.pycharm_helpers/pydev/pydevd.py", line 1534, in _exec

pydev_imports.execfile(file, globals, locals) # execute the script

File "/home/czh/.pycharm_helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile

exec(compile(contents+"\n", file, 'exec'), glob, loc)

File "/home/czh/UAP_VLP-main/Eval_ImgCap_BLIP.py", line 322, in

main(args, config)

File "/home/czh/UAP_VLP-main/Eval_ImgCap_BLIP.py", line 200, in main

t_model = load_eval_model(args.target_model, args.target_ckpt, device)

File "/home/czh/UAP_VLP-main/Eval_ImgCap_BLIP.py", line 148, in load_eval_model

model = load_model("blip2_opt", "caption_coco_opt2.7b", is_eval=True, device=device)

File "/home/czh/UAP_VLP-main/lavis/models/init.py", line 117, in load_model

model = registry.get_model_class(name).from_pretrained(model_type=model_type)

File "/home/czh/UAP_VLP-main/lavis/models/base_model.py", line 70, in from_pretrained

model = cls.from_config(model_cfg)

File "/home/czh/UAP_VLP-main/lavis/models/blip2_models/blip2_opt.py", line 423, in from_config

model.load_checkpoint_from_config(cfg)

File "/home/czh/UAP_VLP-main/lavis/models/base_model.py", line 95, in load_checkpoint_from_config

self.load_checkpoint(url_or_filename=finetune_path)

File "/home/czh/UAP_VLP-main/lavis/models/base_model.py", line 51, in load_checkpoint

msg = self.load_state_dict(state_dict, strict=False)

File "/home/czh/.conda/envs/sam/lib/python3.8/site-packages/torch/nn/modules/module.py", line 2215, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(

RuntimeError: Error(s) in loading state_dict for Blip2OPT:

size mismatch for opt_proj.weight: copying a param with shape torch.Size([2560, 768]) from checkpoint, the shape in current model is torch.Size([768, 768]).

size mismatch for opt_proj.bias: copying a param with shape torch.Size([2560]) from checkpoint, the shape in current model is torch.Size([768]).

error position： self.opt_proj = nn.Linear(self.Qformer.config.hidden_size, self.opt_model.config.hidden_size)