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Merge pull request #867 from DaoyuanLi2816/fix/lora-inference-paths 

[fix] align LoRA inference paths with training output
master
jingyaogong 2026-09-22 23:20:45 +08:00 committed by GitHub
parent 1e6e909f88 4b86522f8a
commit 7da0f92ff6
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2 changed files with 2 additions and 2 deletions
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2
eval_llm.py
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@ -23,7 +23,7 @@ def init_model(args):
model.load_state_dict(torch.load(ckp, map_location=args.device), strict=True)
if args.lora_weight != 'None':
apply_lora(model)
load_lora(model, f'./{args.save_dir}/{args.lora_weight}_{args.hidden_size}.pth')
load_lora(model, f'./{args.save_dir}/{args.lora_weight}_{args.hidden_size}{moe_suffix}.pth')
else:
model = AutoModelForCausalLM.from_pretrained(args.load_from, trust_remote_code=True)
get_model_params(model, model.config)

2
scripts/serve_openai_api.py
View File

@ -40,7 +40,7 @@ def init_model(args):
model.load_state_dict(torch.load(ckp, map_location=device), strict=True)
if args.lora_weight != 'None':
apply_lora(model)
load_lora(model, f'../{args.save_dir}/lora/{args.lora_weight}_{args.hidden_size}.pth')
load_lora(model, f'../{args.save_dir}/{args.lora_weight}_{args.hidden_size}{moe_suffix}.pth')
else:
model = AutoModelForCausalLM.from_pretrained(args.load_from, trust_remote_code=True)
print(f'MiniMind模型参数量: {sum(p.numel() for p in model.parameters()) / 1e6:.2f} M(illion)')