[feat] get params

eval_llm.py

@@ -6,7 +6,7 @@ import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer
 from model.model_minimind import MiniMindConfig, MiniMindForCausalLM
 from model.model_lora import *
-from trainer.trainer_utils import setup_seed
+from trainer.trainer_utils import setup_seed, get_model_params
 warnings.filterwarnings('ignore')
 
 def init_model(args):
@@ -26,7 +26,7 @@ def init_model(args):
             load_lora(model, f'./{args.save_dir}/lora/{args.lora_weight}_{args.hidden_size}.pth')
     else:
         model = AutoModelForCausalLM.from_pretrained(args.load_from, trust_remote_code=True)
-    print(f'MiniMind模型参数: {sum(p.numel() for p in model.parameters()) / 1e6:.2f} M(illion)')
+    get_model_params(model, model.config)
     return model.eval().to(args.device), tokenizer
 
 def main():