[Bug] run deepseek-r1-0528 cpu memory so high

### 检查清单

- [x] 1. 我已经搜索过相关问题，但未能获得预期的帮助
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### 问题描述

loading model.layers.40.self_attn.q_a_layernorm.weight to cuda:2
loading model.layers.40.self_attn.kv_a_layernorm.weight to cuda:2
loading model.layers.40.self_attn.kv_b_proj.weight to cuda:2
loading model.layers.40.input_layernorm.weight to cuda:2
loading model.layers.40.post_attention_layernorm.weight to cuda:2
loading model.layers.41.self_attn.q_a_layernorm.weight to cuda:2
loading model.layers.41.self_attn.kv_a_layernorm.weight to cuda:2
loading model.layers.41.self_attn.kv_b_proj.weight to cuda:2
在加载模型时，memory一致升高，在第41层时，内存占用过高，直接卡掉，内存变为0。（内存总量为1T，可用如下）

### 复现步骤

CUDA_VISIBLE_DEVICES=1,2,3,4 \
python3 ktransformers/server/main.py \
--gguf_path /localnvme/application/lilw/weights/unsloth/DeepSeek-R1-0528-GGUF/Q4_K_M/ \
--model_path /localnvme/application/lilw/weights/deepseek-ai/DeepSeek-R1-0528 \
--model_name DeepSeek-R1-0528-GGUF \
--cpu_infer 128 \
--max_new_tokens 8192 \
--cache_lens 32768 \
--temperature 0.6 \
--top_p 0.95 \
--optimize_config_path ktransformers/optimize/optimize_rules/DeepSeek-V3-Chat-multi-gpu-4.yaml

### 环境信息

GPU:NVIDIA A800 8张
CPU: Intel(R) Xeon(R) Platinum 8358P CPU @ 2.60GHz
操作系统：ubuntu22.04

编译的ktransformers
ktransformers: 0.3.1+cu124torch26fancy

Start with ktransformers/server/main.py and the DeepSeek-V3-Chat-multi-gpu-4.yaml optimization configuration, then reproduce the supplied command with the listed model paths and hardware. Trace memory growth while layers 40 and 41 load; done means the model finishes loading without exhausting host memory or being killed.

Written by the indexing model from the issue text.