{"id":103316,"date":"2026-09-10T08:49:38","date_gmt":"2026-09-10T00:49:38","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/103316.html"},"modified":"2026-09-10T08:49:38","modified_gmt":"2026-09-10T00:49:38","slug":"%e3%80%90sensenova-u1-5-lite%e5%ae%9e%e6%88%98%e3%80%91%e5%90%8c%e4%b8%80%e6%9d%a1%e5%91%bd%e4%bb%a4%ef%bc%8c%e4%b8%ba%e4%bb%80%e4%b9%88-16gb-%e5%8d%a1%e5%bf%85%e5%b4%a9%e3%80%81a100-%e7%a7%92","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/103316.html","title":{"rendered":"\u3010SenseNova U1.5 Lite\u5b9e\u6218\u3011\u540c\u4e00\u6761\u547d\u4ee4\uff0c\u4e3a\u4ec0\u4e48 16GB \u5361\u5fc5\u5d29\u3001A100 \u79d2\u8fc7\uff1f\u2014\u2014WSL2 pinned \u5185\u5b58\u8fb9\u754c\u5b9e\u6d4b"},"content":{"rendered":"<p>\u2003\u2003\u5927\u5bb6\u597d&#xff0c;\u6211\u662fherosunly\u3002985\u9662\u6821\u7855\u58eb\u6bd5\u4e1a&#xff0c;\u73b0\u62c5\u4efb\u7b97\u6cd5\u5de5\u7a0b\u5e08\u4e00\u804c&#xff0c;\u83b7\u5f97CSDN\u535a\u5ba2\u4e4b\u661f\u7b2c\u4e00\u540d&#xff0c;\u70ed\u8877\u4e8e\u5927\u6a21\u578b\u7b97\u6cd5\u7684\u7814\u7a76\u4e0e\u5e94\u7528\u3002\u66fe\u62c5\u4efb\u767e\u5ea6\u5343\u5e06\u5927\u6a21\u578b\u6bd4\u8d5b\u3001\u82f1\u7279\u5c14AI\u5927\u8d5b\u8bc4\u59d4&#xff0c;\u7f16\u5199\u5fae\u8f6fOpenAI\u8003\u8bd5\u8ba4\u8bc1\u6307\u5bfc\u624b\u518c&#xff0c;\u79d1\u5927\u8baf\u98deAI\u5927\u5b66\u5802\u8363\u8a89\u8bb2\u5e08\u3002\u66fe\u83b7\u5f97\u591a\u9879AI\u9876\u7ea7\u6bd4\u8d5b\u7684Top\u540d\u6b21&#xff0c;\u5176\u4e2d\u5305\u62ec\u963f\u91cc\u4e91\u3001\u79d1\u5927\u8baf\u98de\u6bd4\u8d5b\u7b2c\u4e00\u540d&#xff0c;CCF\u3001\u5f00\u653e\u539f\u5b50\u6bd4\u8d5b\u4e8c\u7b49\u5956\u3002\u5728\u6280\u672f\u521b\u65b0\u9886\u57df\u62e5\u6709\u591a\u9879\u6388\u6743\u53d1\u660e\u3002\u66fe\u8f85\u5bfc\u591a\u4f4d\u975e\u79d1\u73ed\u51fa\u8eab\u7684\u540c\u5b66\u6210\u529f\u8fdb\u5165\u7b97\u6cd5\u884c\u4e1a\u5c31\u4e1a\u3002\u5e0c\u671b\u548c\u5927\u5bb6\u4e00\u8d77\u6210\u957f\u8fdb\u6b65\u3002<\/p>\n<p>\u2003\u2003\u8fd9\u6b21\u5728 RTX 5060 Ti 16GB \u4e0a\u8fd0\u884c SenseNova U1.5&#xff0c;\u6211\u8fde\u7eed\u9047\u5230\u4e86\u4e09\u6b21 OOM\u3002\u8c03\u6574\u663e\u5b58\u6863\u4f4d\u3001\u6362\u6570\u636e\u7c7b\u578b&#xff0c;\u90fd\u6ca1\u80fd\u89e3\u51b3\u3002\u5947\u602a\u7684\u662f&#xff0c;\u62a5\u9519\u65f6 GPU \u663e\u5b58\u5e76\u6ca1\u6709\u7528\u6ee1\u3002\u7ee7\u7eed\u8ffd\u8e2a\u8c03\u7528\u6808&#xff0c;\u95ee\u9898\u843d\u5728\u4e86 pin_memory()&#xff1a;\u5b98\u65b9 layer offload \u8def\u5f84\u9700\u8981\u9501\u5b9a\u4e3b\u673a\u5185\u5b58&#xff0c;\u800c WSL2 \u5728\u63a2\u6d4b\u4e2d\u7d2f\u8ba1\u6210\u529f\u5206\u914d\u5230 31 GiB \u540e&#xff0c;\u4fbf\u65e0\u6cd5\u7ee7\u7eed\u5206\u914d\u3002\u6a21\u578b\u7684 BF16 \u6743\u91cd\u7ea6\u4e3a 32.7 GiB&#xff0c;\u521d\u59cb\u5316\u8fc7\u4e0d\u53bb&#xff0c;\u540e\u9762\u7684\u63a8\u7406\u53c2\u6570\u81ea\u7136\u4e5f\u65e0\u4ece\u8c08\u8d77\u3002\u4e3a\u4e86\u786e\u8ba4\u95ee\u9898&#xff0c;\u6211\u53c8\u5728\u539f\u751f Linux \u7684 A100 40GB \u73af\u5883\u4e2d\u505a\u4e86\u5bf9\u7167\u3002\u968f\u540e\u56de\u5230\u672c\u5730&#xff0c;\u6539\u7528 Accelerate \u7684 sequential offload&#xff0c;\u7ec8\u4e8e\u8ba9\u540c\u4e00\u5f20 16GB \u5361\u5b8c\u6210\u4e86\u751f\u6210\u3002\u642d\u914d\u5b98\u65b9 8 \u6b65\u84b8\u998f LoRA \u540e&#xff0c;\u672c\u6b21\u6d4b\u8bd5\u4e2d&#xff0c;2048\u00d72048 \u56fe\u50cf\u7684\u751f\u6210\u8017\u65f6\u4ece\u7ea6 7.3 \u5206\u949f\u964d\u5230\u4e86\u7ea6 48 \u79d2\u3002\u4e0b\u9762\u6309\u5b9e\u9645\u6392\u67e5\u987a\u5e8f\u5c55\u5f00&#xff1a;\u5148\u770b\u62a5\u9519\u53d1\u751f\u5728\u54ea\u91cc&#xff0c;\u518d\u770b\u4e24\u5957\u73af\u5883\u7684\u5dee\u5f02&#xff0c;\u4ee5\u53ca\u6362\u4e00\u6761\u63a8\u7406\u8def\u5f84\u540e&#xff0c;\u901f\u5ea6\u548c\u8f93\u51fa\u8d28\u91cf\u5206\u522b\u600e\u6837\u3002<\/p>\n<\/p>\n<h4>\u6587\u7ae0\u76ee\u5f55<\/h4>\n<ul>\n<li>1. \u90e8\u7f72\u5b9e\u6218&#xff1a;WSL2 OOM \u6392\u67e5\u4e0e\u66ff\u4ee3\u65b9\u6848<\/li>\n<li>\n<ul>\n<li>1.1 \u6a21\u578b\u4f53\u91cf\u4e0e\u5b9e\u9a8c\u73af\u5883<\/li>\n<li>1.2 \u62a5\u9519\u5b9a\u4f4d\u4e0e\u53c2\u6570\u6392\u67e5<\/li>\n<li>1.3 \u9875\u9501\u5b9a\u5185\u5b58\u5bb9\u91cf\u63a2\u6d4b<\/li>\n<li>1.4 A100 \u5bf9\u7167&#xff1a;\u521d\u59cb\u5316\u7ed3\u679c\u4e0e\u5185\u5b58\u5f00\u9500<\/li>\n<li>1.5 \u672c\u5730\u8dd1\u901a&#xff1a;sequential offload \u4e0e 8 \u6b65 LoRA<\/li>\n<\/ul>\n<\/li>\n<li>2. A100 \u5b9e\u6d4b&#xff1a;\u63a8\u7406\u901f\u5ea6\u4e0e\u751f\u6210\u8d28\u91cf<\/li>\n<li>\n<ul>\n<li>2.1 \u4e0d\u540c\u4efb\u52a1\u7684\u52a0\u901f\u6548\u679c<\/li>\n<li>2.2 \u6587\u5b57\u8d28\u91cf\u4e0e\u7ea6\u675f\u9075\u5faa<\/li>\n<li>2.3 \u5206\u8fa8\u7387\u6d4b\u8bd5&#xff1a;4.2MP \u4e0e UHD<\/li>\n<li>2.4 \u957f\u6307\u4ee4\u6d4b\u8bd5&#xff1a;\u7ec6\u7c92\u5ea6\u7ea6\u675f\u7684\u6267\u884c\u60c5\u51b5<\/li>\n<\/ul>\n<\/li>\n<li>3. \u5f02\u5e38\u8f93\u51fa\u6392\u67e5&#xff1a;\u4e00\u6b21\u672a\u590d\u73b0\u7684\u5168\u9ed1\u56fe\u50cf<\/li>\n<li>4. \u603b\u7ed3\u4e0e\u90e8\u7f72\u5efa\u8bae<\/li>\n<\/ul>\n<h2>1. \u90e8\u7f72\u5b9e\u6218&#xff1a;WSL2 OOM \u6392\u67e5\u4e0e\u66ff\u4ee3\u65b9\u6848<\/h2>\n<h3>1.1 \u6a21\u578b\u4f53\u91cf\u4e0e\u5b9e\u9a8c\u73af\u5883<\/h3>\n<p>\u2003\u2003\u672c\u6587\u4f7f\u7528\u7684\u68c0\u67e5\u70b9\u662f SenseNova-U1.5-8B-MoT\u3002\u540d\u79f0\u4e2d\u7684\u201c8B\u201d\u4e0d\u80fd\u76f4\u63a5\u5f53\u4f5c\u6574\u4efd\u68c0\u67e5\u70b9\u7684\u53c2\u6570\u91cf\u3002\u6309\u672c\u6b21\u4f7f\u7528\u7684\u6743\u91cd\u7edf\u8ba1&#xff0c;\u6a21\u578b\u7ea6\u6709 17.53B \u53c2\u6570&#xff0c;BF16 \u6743\u91cd\u7ea6\u5360 32.7 GiB&#xff0c;\u5206\u4e3a 8 \u4e2a\u6587\u4ef6\u3002\u8fd9\u6837\u7684\u6743\u91cd\u5927\u5c0f\u65e0\u6cd5\u5b8c\u6574\u9a7b\u7559\u5728 16GB \u663e\u5361\u4e0a\u3002\u8981\u8fd0\u884c\u5b83&#xff0c;\u9700\u8981\u91cf\u5316\u3001\u5378\u8f7d\u7b49\u989d\u5916\u65b9\u6848&#xff0c;\u4ec5\u8c03\u6574\u751f\u6210\u5206\u8fa8\u7387\u6216\u6b65\u6570\u5e76\u4e0d\u80fd\u8ba9\u6743\u91cd\u672c\u8eab\u53d8\u5c0f\u3002 \u2003\u2003\u5b98\u65b9\u811a\u672c\u63d0\u4f9b\u4e86 layer_offload \u8def\u5f84&#xff1a;\u5c06\u6743\u91cd\u4fdd\u5b58\u5728\u4e3b\u673a\u5185\u5b58\u4e2d&#xff0c;\u4f7f\u7528 pin_memory() \u5206\u914d\u9875\u9501\u5b9a\u5185\u5b58&#xff0c;\u63a8\u7406\u65f6\u518d\u6309\u9700\u5c06\u5c42\u642c\u5230 GPU\u3002\u8fd9\u53ef\u4ee5\u8282\u7701\u663e\u5b58&#xff0c;\u4f46\u4e3b\u673a\u4fa7\u4e5f\u8981\u627f\u62c5\u76f8\u5e94\u7684\u5185\u5b58\u5f00\u9500\u3002\u6211\u9009\u62e9 WSL2&#xff0c;\u662f\u56e0\u4e3a\u672c\u5730\u4f7f\u7528 Windows&#xff0c;\u800c\u63a8\u7406\u6808\u4e3b\u8981\u57fa\u4e8e Linux \u751f\u6001\u3002\u5bf9\u4e8e\u4e0d\u60f3\u5355\u72ec\u5b89\u88c5 Linux \u7684\u7528\u6237&#xff0c;WSL2 \u662f\u4e00\u4e2a\u65b9\u4fbf\u7684\u9009\u62e9\u3002\u4e0d\u8fc7&#xff0c;\u8fd9\u6b21\u5b9e\u9a8c\u4e5f\u8bf4\u660e&#xff0c;\u80fd\u8fd0\u884c Linux \u7528\u6237\u6001\u7a0b\u5e8f&#xff0c;\u5e76\u4e0d\u610f\u5473\u7740\u5b83\u7684 GPU \u5185\u5b58\u884c\u4e3a\u4e0e\u539f\u751f Linux \u5b8c\u5168\u76f8\u540c\u3002<\/p>\n<table>\n<tr>\u9879\u76ee\u672c\u5730\u73af\u5883\u4e91\u7aef\u73af\u5883<\/tr>\n<tbody>\n<tr>\n<td>GPU<\/td>\n<td>RTX 5060 Ti 16GB<\/td>\n<td>A100-PCIE-40GB<\/td>\n<\/tr>\n<tr>\n<td>\u9a71\u52a8<\/td>\n<td>610.62<\/td>\n<td>595.71.05<\/td>\n<\/tr>\n<tr>\n<td>\u7cfb\u7edf<\/td>\n<td>Windows 11 build 26200 &#043; WSL2&#xff0c;\u5185\u6838 6.6.87.2<\/td>\n<td>Ubuntu 22.04.5 LTS<\/td>\n<\/tr>\n<tr>\n<td>Python<\/td>\n<td>3.11.15<\/td>\n<td>3.11.16<\/td>\n<\/tr>\n<tr>\n<td>PyTorch \/ CUDA<\/td>\n<td>2.8.0&#043;cu128 \/ 12.8<\/td>\n<td>2.8.0&#043;cu128 \/ 12.8<\/td>\n<\/tr>\n<tr>\n<td>\u4e3b\u673a\u5185\u5b58\u914d\u989d<\/td>\n<td>\u57fa\u7ebf\u914d\u7f6e 44 GiB<\/td>\n<td>cgroup 72 GiB \/ 10 \u6838<\/td>\n<\/tr>\n<tr>\n<td>\u6a21\u578b\u6743\u91cd<\/td>\n<td>8 \u5206\u7247&#xff0c;BF16&#xff0c;\u7ea6 32.7 GiB<\/td>\n<td>\u540c\u4e00\u4efd\u6743\u91cd<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u2003\u2003\u672c\u5730\u73af\u5883\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u68c0\u67e5&#xff1a;<\/p>\n<p><span class=\"token function\">uname<\/span> <span class=\"token parameter variable\">-r<\/span><br \/>\n<span class=\"token comment\"># 6.6.87.2-microsoft-standard-WSL2<\/span><\/p>\n<p>nvidia-smi<br \/>\n<span class=\"token comment\"># RTX 5060 Ti 16GB, driver 610.62<\/span><\/p>\n<p>python <span class=\"token parameter variable\">-c<\/span> <span class=\"token string\">&#034;import torch; print(torch.__version__, torch.version.cuda, torch.cuda.get_device_name(0))&#034;<\/span><br \/>\n<span class=\"token comment\"># 2.8.0&#043;cu128  12.8  NVIDIA GeForce RTX 5060 Ti<\/span><\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004926-6aa1fe96d6e22.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h3>1.2 \u62a5\u9519\u5b9a\u4f4d\u4e0e\u53c2\u6570\u6392\u67e5<\/h3>\n<p>\u2003\u2003\u770b\u5230 OOM&#xff0c;\u6211\u5148\u5c1d\u8bd5\u964d\u4f4e\u663e\u5b58\u6863\u4f4d&#xff0c;\u518d\u5c06 bfloat16 \u6362\u6210 float16\u3002\u4e09\u79cd\u7ec4\u5408\u7684\u7ed3\u679c\u76f8\u540c&#xff1a;<\/p>\n<table>\n<tr>\u53c2\u6570\u7ec4\u5408\u8fd0\u884c\u7ed3\u679c<\/tr>\n<tbody>\n<tr>\n<td>balanced &#043; bfloat16<\/td>\n<td>pin_memory() \u89e6\u53d1 CUDA OOM<\/td>\n<\/tr>\n<tr>\n<td>low &#043; bfloat16<\/td>\n<td>\u540c\u4e0a<\/td>\n<\/tr>\n<tr>\n<td>low &#043; float16<\/td>\n<td>\u540c\u4e0a<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u2003\u2003\u5176\u4e2d\u4e00\u6b21\u8fd0\u884c\u547d\u4ee4\u5982\u4e0b&#xff1a;<\/p>\n<p>python examples\/t2i\/inference.py <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;model_path<\/span> \/root\/models\/snapshots\/master <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;prompt<\/span> <span class=\"token string\">&#034;A clean bilingual technology infographic about local AI deployment.&#034;<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;width<\/span> <span class=\"token number\">1024<\/span> <span class=\"token parameter variable\">&#8211;height<\/span> <span class=\"token number\">1024<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;vram_mode<\/span> balanced <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;dtype<\/span> bfloat16 <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;seed<\/span> <span class=\"token number\">42<\/span><\/p>\n<p><span class=\"token comment\"># torch.AcceleratorError: CUDA error: out of memory<\/span><br \/>\n<span class=\"token comment\">#   at src\/sensenova_u1\/utils\/layer_offload.py:317 (pin_memory)<\/span><\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004927-6aa1fe970e909.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u2003\u2003\u95ee\u9898\u5728\u4e8e&#xff0c;\u62a5\u9519\u65f6\u89c2\u5bdf\u5230\u7684 GPU \u663e\u5b58\u5360\u7528\u8fdc\u4f4e\u4e8e 16GB\u3002\u8c03\u7528\u6808\u4e2d\u7684 pin_memory() \u64cd\u4f5c\u7684\u662f\u4e3b\u673a\u4fa7\u7684\u9875\u9501\u5b9a\u5185\u5b58&#xff0c;\u56e0\u6b64\u8fd9\u91cc\u4e0d\u80fd\u53ea\u51ed\u201cCUDA OOM\u201d\u51e0\u4e2a\u5b57&#xff0c;\u5c31\u8ba4\u5b9a GPU \u663e\u5b58\u4e0d\u8db3\u3002 \u2003\u2003\u6e90\u7801\u4e5f\u89e3\u91ca\u4e86\u4e3a\u4ec0\u4e48\u6362\u6863\u4f4d\u6ca1\u6709\u89e3\u51b3\u95ee\u9898\u3002_LayerStore.__init__ \u5728\u521d\u59cb\u5316\u5c42\u5b58\u50a8\u65f6&#xff0c;\u4f1a\u5bf9\u5c42\u5f20\u91cf\u8c03\u7528 pin_memory()\u3002\u8c03\u6574\u9884\u53d6\u5c42\u6570\u53ef\u4ee5\u5f71\u54cd\u63a8\u7406\u9636\u6bb5\u7684\u642c\u8fd0\u884c\u4e3a&#xff0c;\u5374\u6ca1\u6709\u7ed5\u5f00\u8fd9\u4e00\u521d\u59cb\u5316\u8fc7\u7a0b\u3002bfloat16 \u548c float16 \u53c8\u540c\u4e3a 16 \u4f4d\u683c\u5f0f&#xff0c;\u5207\u6362\u540e\u4e0d\u4f1a\u51cf\u5c11\u8fd9\u90e8\u5206\u6743\u91cd\u7684\u5b58\u50a8\u4f53\u79ef\u3002\u5230\u8fd9\u91cc&#xff0c;\u7ee7\u7eed\u8c03\u6574\u751f\u6210\u53c2\u6570\u7684\u610f\u4e49\u5df2\u7ecf\u4e0d\u5927\u3002\u6211\u628a\u6392\u67e5\u91cd\u70b9\u8f6c\u5230\u4e86\u4e3b\u673a\u4fa7&#xff1a;\u8fd9\u53f0\u673a\u5668\u7a76\u7adf\u80fd\u5206\u914d\u591a\u5c11\u9875\u9501\u5b9a\u5185\u5b58&#xff1f;<\/p>\n<h3>1.3 \u9875\u9501\u5b9a\u5185\u5b58\u5bb9\u91cf\u63a2\u6d4b<\/h3>\n<p>\u2003\u2003\u63a2\u6d4b\u7528\u4e86\u4e24\u6761\u8def\u5f84&#xff1a;\u4e00\u6761\u901a\u8fc7 PyTorch \u7684 pin_memory() \u9010\u5757\u5206\u914d&#xff0c;\u53e6\u4e00\u6761\u76f4\u63a5\u8c03\u7528 CUDA driver API \u7684 cuMemHostAlloc\u3002\u524d\u8005\u7684\u6838\u5fc3\u4ee3\u7801\u5982\u4e0b&#xff1a;<\/p>\n<p><span class=\"token comment\"># scripts\/probe_pin_memory.py&#xff08;\u8282\u9009&#xff09;<\/span><br \/>\n<span class=\"token keyword\">def<\/span> <span class=\"token function\">probe_torch<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    gb <span class=\"token operator\">&#061;<\/span> <span class=\"token number\">0.0<\/span><br \/>\n    chunks <span class=\"token operator\">&#061;<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token punctuation\">]<\/span><br \/>\n    <span class=\"token keyword\">while<\/span> <span class=\"token boolean\">True<\/span><span class=\"token punctuation\">:<\/span><br \/>\n        <span class=\"token keyword\">try<\/span><span class=\"token punctuation\">:<\/span><br \/>\n            t <span class=\"token operator\">&#061;<\/span> torch<span class=\"token punctuation\">.<\/span>empty<span class=\"token punctuation\">(<\/span><br \/>\n                <span class=\"token number\">256<\/span> <span class=\"token operator\">*<\/span> <span class=\"token number\">1024<\/span> <span class=\"token operator\">*<\/span> <span class=\"token number\">1024<\/span><span class=\"token punctuation\">,<\/span><br \/>\n                dtype<span class=\"token operator\">&#061;<\/span>torch<span class=\"token punctuation\">.<\/span>uint8<br \/>\n            <span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">.<\/span>pin_memory<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><br \/>\n            chunks<span class=\"token punctuation\">.<\/span>append<span class=\"token punctuation\">(<\/span>t<span class=\"token punctuation\">)<\/span><br \/>\n            gb <span class=\"token operator\">&#043;&#061;<\/span> <span class=\"token number\">0.25<\/span><br \/>\n        <span class=\"token keyword\">except<\/span> RuntimeError<span class=\"token punctuation\">:<\/span><br \/>\n            <span class=\"token keyword\">break<\/span><br \/>\n    <span class=\"token keyword\">return<\/span> gb<\/p>\n<p><span class=\"token keyword\">def<\/span> <span class=\"token function\">probe_driver<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span><br \/>\n    <span class=\"token comment\"># \u901a\u8fc7 cuMemHostAlloc \u9010\u6b21\u5206\u914d&#xff0c;\u5e76\u8bb0\u5f55\u5931\u8d25\u70b9\u3002<\/span><br \/>\n    <span class=\"token comment\"># \u6b64\u5904\u7701\u7565\u9a71\u52a8\u521d\u59cb\u5316\u548c\u5206\u914d\u4ee3\u7801\u3002<\/span><br \/>\n    <span class=\"token punctuation\">.<\/span><span class=\"token punctuation\">.<\/span><span class=\"token punctuation\">.<\/span><\/p>\n<p>\u2003\u2003\u4e24\u6761\u8def\u5f84\u7684\u8bb0\u5f55\u4e00\u81f4&#xff1a;\u7d2f\u8ba1\u6210\u529f\u5206\u914d 31.000 GiB&#xff0c;\u5373 31744 MiB \u540e&#xff0c;\u7ee7\u7eed\u5206\u914d\u5931\u8d25\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004928-6aa1fe980cbd9.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u2003\u2003\u8fd9\u4e2a\u7ed3\u679c\u5c06\u95ee\u9898\u8fdb\u4e00\u6b65\u7f29\u5c0f\u5230\u4e86\u5f53\u524d\u73af\u5883\u4e2d\u7684\u4e3b\u673a\u9875\u9501\u5b9a\u5185\u5b58\u5206\u914d\u9650\u5236&#xff0c;\u4f46\u8fd8\u4e0d\u80fd\u76f4\u63a5\u89e3\u91ca\u9650\u5236\u6765\u81ea\u54ea\u91cc\u3002\u2003\u6392\u67e5\u4e2d&#xff0c;\u6211\u4e5f\u5bf9\u6bd4\u4e86\u201c\u663e\u5b58\u5bb9\u91cf\u7684\u4e24\u500d\u201d\u548c\u201c\u7269\u7406\u5185\u5b58\u7684\u4e00\u534a\u201d\u7b49\u4f30\u7b97\u65b9\u5f0f&#xff0c;\u5b83\u4eec\u4e0e\u672c\u6b21\u6d4b\u5f97\u7684\u6570\u503c\u5e76\u4e0d\u543b\u5408\u3002\u8bbe\u5907\u5c5e\u6027\u4e2d\u7684 PageableMemoryAccess&#061;0 \u7b49\u4fe1\u606f&#xff0c;\u53ef\u4ee5\u5e2e\u52a9\u7406\u89e3\u5f53\u524d\u73af\u5883\u7684\u5185\u5b58\u8bbf\u95ee\u80fd\u529b&#xff0c;\u5374\u4e0d\u8db3\u4ee5\u5355\u72ec\u8bc1\u660e\u5b58\u5728\u4e00\u4e2a\u56fa\u5b9a\u4e3a 31 GiB \u7684\u5185\u6838\u914d\u989d\u3002\u8fd9\u91cc\u9700\u8981\u628a\u89c2\u6d4b\u4e0e\u63a8\u6d4b\u5206\u5f00&#xff1a;31 GiB \u662f\u672c\u673a\u5728\u5f53\u524d\u6d4b\u8bd5\u6761\u4ef6\u4e0b\u6210\u529f\u5206\u914d\u5230\u7684\u5bb9\u91cf&#xff0c;\u4e0d\u662f\u6240\u6709 WSL2 \u73af\u5883\u90fd\u9002\u7528\u7684\u4e0a\u9650\u3002 \u63a2\u6d4b\u672c\u8eab\u8fd8\u6709\u5206\u914d\u6b65\u957f&#xff0c;\u65e5\u5fd7\u663e\u793a\u5230\u4e09\u4f4d\u5c0f\u6570&#xff0c;\u4e5f\u4e0d\u4ee3\u8868\u5df2\u7ecf\u83b7\u5f97\u540c\u7b49\u7cbe\u5ea6\u7684\u6781\u9650\u503c\u3002\u5bf9\u8fd9\u6b21\u90e8\u7f72\u800c\u8a00&#xff0c;\u5df2\u6709\u4fe1\u606f\u8db3\u591f\u6307\u5bfc\u4e0b\u4e00\u6b65&#xff1a;\u6a21\u578b BF16 \u6743\u91cd\u7ea6\u4e3a 32.7 GiB&#xff0c;\u800c\u5f53\u524d\u5206\u914d\u6d4b\u8bd5\u5728 31 GiB \u540e\u5931\u8d25&#xff0c;\u7ee7\u7eed\u4f7f\u7528\u8fd9\u6761\u521d\u59cb\u5316\u8def\u5f84\u5f88\u96be\u8dd1\u901a\u3002\u81f3\u4e8e\u9650\u5236\u7a76\u7adf\u6765\u81ea WSL2\u3001\u9a71\u52a8\u8fd8\u662f\u5176\u4ed6\u8d44\u6e90\u7ba1\u7406\u73af\u8282&#xff0c;\u8fd8\u9700\u8981\u66f4\u5e95\u5c42\u7684\u8bc1\u636e\u3002<\/p>\n<h3>1.4 A100 \u5bf9\u7167&#xff1a;\u521d\u59cb\u5316\u7ed3\u679c\u4e0e\u5185\u5b58\u5f00\u9500<\/h3>\n<p>\u2003\u2003\u63a5\u4e0b\u6765&#xff0c;\u6211\u5c06\u540c\u4e00\u4efd\u6743\u91cd\u653e\u5230\u539f\u751f Linux \u7684 A100 \u73af\u5883&#xff0c;\u4f7f\u7528\u76f8\u540c\u63d0\u793a\u8bcd\u3001\u968f\u673a\u79cd\u5b50\u548c\u5206\u8fa8\u7387\u8fdb\u884c\u5bf9\u7167\u3002\u4e24\u7aef\u4ee3\u7801\u7248\u672c\u4e5f\u505a\u4e86\u68c0\u67e5&#xff1a;\u672c\u5730\u4e3a 022fa66&#xff0c;\u4e91\u7aef\u4e3a e2edb8b&#xff0c;\u4e2d\u95f4\u53ea\u6709\u4e24\u4e2a\u6587\u6863\u63d0\u4ea4&#xff0c;\u76f8\u5173\u7684 layer_offload.py \u6ca1\u6709\u53d8\u5316\u3002\u4e91\u7aef\u547d\u4ee4\u5c06\u90e8\u5206\u63a8\u7406\u53c2\u6570\u663e\u5f0f\u5217\u51fa&#xff1a;<\/p>\n<p>python examples\/t2i\/inference.py <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;model_path<\/span> \/root\/autodl-tmp\/SenseNova-U1.5-8B-MoT <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;prompt<\/span> <span class=\"token string\">&#034;A clean bilingual technology infographic about local AI deployment.&#034;<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;width<\/span> <span class=\"token number\">1024<\/span> <span class=\"token parameter variable\">&#8211;height<\/span> <span class=\"token number\">1024<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;vram_mode<\/span> balanced <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;cfg_scale<\/span> <span class=\"token number\">4.0<\/span> <span class=\"token parameter variable\">&#8211;cfg_norm<\/span> none <span class=\"token parameter variable\">&#8211;timestep_shift<\/span> <span class=\"token number\">3.0<\/span> <span class=\"token parameter variable\">&#8211;num_steps<\/span> <span class=\"token number\">50<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;seed<\/span> <span class=\"token number\">42<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;output<\/span> \/root\/autodl-tmp\/outputs\/contrast-balanced-50.png <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;profile<\/span><\/p>\n<p>\u2003\u2003\u8fd9\u6b21\u6210\u529f\u901a\u8fc7\u4e86 pin_memory() \u9636\u6bb5&#xff0c;\u5e76\u5b8c\u6210\u751f\u6210&#xff1a;<\/p>\n<table>\n<tr>\u6307\u6807\u7ed3\u679c<\/tr>\n<tbody>\n<tr>\n<td>pin_memory() \u521d\u59cb\u5316<\/td>\n<td>\u901a\u8fc7<\/td>\n<\/tr>\n<tr>\n<td>\u6a21\u578b\u52a0\u8f7d\u8017\u65f6<\/td>\n<td>2.245s<\/td>\n<\/tr>\n<tr>\n<td>\u751f\u6210\u8017\u65f6&#xff0c;50 \u6b65\u30011024\u00d71024<\/td>\n<td>257.946s<\/td>\n<\/tr>\n<tr>\n<td>\u5cf0\u503c GPU allocated \/ reserved<\/td>\n<td>3.64 \/ 6.98 GiB<\/td>\n<\/tr>\n<tr>\n<td>\u5cf0\u503c\u4e3b\u673a RSS<\/td>\n<td>51.49 GiB<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004928-6aa1fe9874547.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u2003\u2003\u8fd9\u7ec4\u7ed3\u679c\u8bf4\u660e&#xff0c;\u76f8\u5e94\u4ee3\u7801\u8def\u5f84\u53ef\u4ee5\u5728\u53e6\u4e00\u5957\u73af\u5883\u4e2d\u8fd0\u884c\u3002\u4f46\u4e24\u7aef\u7684 GPU\u3001\u9a71\u52a8\u548c\u5185\u5b58\u914d\u7f6e\u90fd\u4e0d\u540c&#xff0c;\u56e0\u6b64\u8fd9\u4e0d\u662f\u5355\u72ec\u9694\u79bb\u4e86 WSL2 \u56e0\u7d20\u7684\u5b9e\u9a8c&#xff0c;\u4e0d\u80fd\u636e\u6b64\u6392\u9664\u6240\u6709\u4ee3\u7801\u4e0e\u73af\u5883\u4e4b\u95f4\u7684\u517c\u5bb9\u6027\u95ee\u9898\u3002\u53e6\u4e00\u4e2a\u503c\u5f97\u7559\u610f\u7684\u6570\u5b57\u662f 51.49 GiB\u3002\u7701\u4e0b\u6765\u7684\u663e\u5b58\u5e76\u6ca1\u6709\u51ed\u7a7a\u6d88\u5931&#xff0c;\u4e3b\u673a\u5185\u5b58\u627f\u62c5\u4e86\u76f8\u5f53\u4e00\u90e8\u5206\u5f00\u9500\u3002\u8fd9\u4e2a\u5cf0\u503c\u9ad8\u4e8e\u672c\u5730\u57fa\u7ebf\u914d\u7f6e\u7684 44 GiB&#xff0c;\u5373\u4f7f\u89e3\u51b3\u9875\u9501\u5b9a\u5185\u5b58\u5206\u914d\u95ee\u9898&#xff0c;\u4e5f\u4ecd\u9700\u68c0\u67e5\u4e3b\u673a\u603b\u5185\u5b58\u662f\u5426\u8db3\u591f\u3002\u6392\u67e5\u671f\u95f4\u5c1d\u8bd5\u8c03\u5927 .wslconfig \u7684\u5185\u5b58\u8bbe\u7f6e&#xff0c;\u4e5f\u6ca1\u6709\u89e3\u51b3\u6700\u5148\u51fa\u73b0\u7684\u5206\u914d\u5931\u8d25\u3002\u7531\u4e8e A100 40GB \u80fd\u5bb9\u7eb3\u8fd9\u4efd\u6a21\u578b&#xff0c;\u6211\u53c8\u8865\u6d4b\u4e86\u6743\u91cd\u5b8c\u6574\u9a7b\u7559\u663e\u5b58\u7684 full \u6a21\u5f0f&#xff1a;<\/p>\n<table>\n<tr>\u6307\u6807balanced&#xff0c;\u5c42\u5378\u8f7dfull&#xff0c;\u663e\u5b58\u9a7b\u7559<\/tr>\n<tbody>\n<tr>\n<td>\u6a21\u578b\u52a0\u8f7d<\/td>\n<td>2.245s<\/td>\n<td>43.217s<\/td>\n<\/tr>\n<tr>\n<td>\u751f\u6210&#xff0c;50 \u6b65\u30011024\u00d71024<\/td>\n<td>257.946s<\/td>\n<td>15.774s<\/td>\n<\/tr>\n<tr>\n<td>\u5cf0\u503c GPU allocated<\/td>\n<td>3.64 GiB<\/td>\n<td>33.28 GiB<\/td>\n<\/tr>\n<tr>\n<td>\u5cf0\u503c\u4e3b\u673a RSS<\/td>\n<td>51.49 GiB<\/td>\n<td>14.08 GiB<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u2003\u2003full \u6a21\u5f0f\u524d\u671f\u52a0\u8f7d\u66f4\u6162&#xff0c;\u4f46\u751f\u6210\u9636\u6bb5\u7ea6\u5feb\u4e86 16.4 \u500d\u3002\u5bf9\u4e8e\u9700\u8981\u53cd\u590d\u51fa\u56fe\u7684\u4efb\u52a1&#xff0c;\u8fd9\u79cd\u5dee\u5f02\u8fdc\u6bd4\u5355\u6b21\u52a0\u8f7d\u8017\u65f6\u66f4\u91cd\u8981\u3002\u5c42\u5378\u8f7d\u89e3\u51b3\u4e86\u663e\u5b58\u4e0d\u8db3\u7684\u95ee\u9898&#xff0c;\u540c\u65f6\u4e5f\u5e26\u6765\u4e86\u6301\u7eed\u7684\u6570\u636e\u642c\u8fd0\u5f00\u9500\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004928-6aa1fe98b0e05.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<h3>1.5 \u672c\u5730\u8dd1\u901a&#xff1a;sequential offload \u4e0e 8 \u6b65 LoRA<\/h3>\n<p>\u2003\u2003\u786e\u8ba4\u539f\u6765\u7684\u8def\u5f84\u5728\u672c\u673a\u53d7\u963b\u540e&#xff0c;\u6211\u6ca1\u6709\u7ee7\u7eed\u56f4\u7ed5 &#8211;vram_mode \u8c03\u53c2&#xff0c;\u800c\u662f\u6539\u7528\u4e86 &#8211;device_map sequential\u3002\u8fd9\u6761 Accelerate dispatch \u8def\u5f84\u4e0d\u7ecf\u8fc7\u524d\u9762\u5931\u8d25\u7684\u5b98\u65b9 _LayerStore \u521d\u59cb\u5316\u8fc7\u7a0b&#xff0c;\u672c\u6b21\u5728\u540c\u4e00\u5f20 16GB \u5361\u4e0a\u5b8c\u6210\u4e86\u751f\u6210\u3002\u4ee5\u4e0b\u662f 2048\u00d72048 \u5206\u8fa8\u7387\u3001\u642d\u914d\u5b98\u65b9 8 \u6b65\u84b8\u998f LoRA \u7684\u914d\u7f6e&#xff1a;<\/p>\n<p>python examples\/t2i\/inference.py <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;model_path<\/span> \/root\/models\/snapshots\/master <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;lora_path<\/span> \/root\/models\/loras\/SenseNova-U1.5-8B-MoT-LoRA-8step.safetensors <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;device_map<\/span> sequential <span class=\"token parameter variable\">&#8211;max_memory<\/span> <span class=\"token string\">&#034;0&#061;14GiB,cpu&#061;40GiB&#034;<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;dtype<\/span> bfloat16 <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;cfg_scale<\/span> <span class=\"token number\">1.0<\/span> <span class=\"token parameter variable\">&#8211;num_steps<\/span> <span class=\"token number\">8<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;width<\/span> <span class=\"token number\">2048<\/span> <span class=\"token parameter variable\">&#8211;height<\/span> <span class=\"token number\">2048<\/span> <span class=\"token parameter variable\">&#8211;seed<\/span> <span class=\"token number\">42<\/span><\/p>\n<p>\u2003\u2003\u4e3a\u4e86\u89c2\u5bdf\u52a0\u901f\u6548\u679c&#xff0c;\u6211\u5728\u76f8\u540c\u63d0\u793a\u8bcd\u3001\u968f\u673a\u79cd\u5b50\u548c\u5206\u8fa8\u7387\u4e0b&#xff0c;\u5bf9\u6bd4\u4e86 Base-50 \u4e0e LoRA-8\u3002\u4e24\u8005\u5206\u522b\u4f7f\u7528\u5bf9\u5e94\u7684\u63a8\u7406\u914d\u7f6e&#xff1a;Base \u4e3a 50 \u6b65\u3001cfg_scale&#061;4.0&#xff0c;LoRA \u4e3a 8 \u6b65\u3001cfg_scale&#061;1.0\u3002\u56e0\u6b64&#xff0c;\u8fd9\u91cc\u6bd4\u8f83\u7684\u662f\u4e24\u5957\u53ef\u7528\u914d\u7f6e\u7684\u5b9e\u9645\u8017\u65f6&#xff0c;\u4e0d\u662f\u53ea\u6539\u53d8 LoRA \u4e00\u4e2a\u53d8\u91cf\u3002<\/p>\n<table>\n<tr>\u6307\u6807Base-50LoRA-8<\/tr>\n<tbody>\n<tr>\n<td>\u751f\u6210\u8017\u65f6<\/td>\n<td>436.969s<\/td>\n<td>47.917s<\/td>\n<\/tr>\n<tr>\n<td>\u65e5\u5fd7\u541e\u5410<\/td>\n<td>9.37 tok\/s<\/td>\n<td>85.48 tok\/s<\/td>\n<\/tr>\n<tr>\n<td>\u5cf0\u503c GPU reserved<\/td>\n<td>15.45 GiB<\/td>\n<td>14.41 GiB<\/td>\n<\/tr>\n<tr>\n<td>CPU RSS<\/td>\n<td>28.96 GiB<\/td>\n<td>28.92 GiB<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u2003\u2003\u5355\u5f20\u56fe\u50cf\u4ece\u7ea6 7.3 \u5206\u949f\u7f29\u77ed\u5230\u7ea6 48 \u79d2&#xff0c;\u52a0\u901f\u6bd4\u4e3a 9.12\u00d7\u3002\u4e3b\u673a\u5185\u5b58\u5360\u7528\u57fa\u672c\u6301\u5e73&#xff0c;\u5cf0\u503c reserved \u4e5f\u7565\u6709\u4e0b\u964d\u3002\u5bf9\u4e8e\u672c\u5730\u8bd5\u63d0\u793a\u8bcd\u3001\u6311\u9009\u6784\u56fe&#xff0c;\u8fd9\u4e2a\u7b49\u5f85\u65f6\u95f4\u5df2\u7ecf\u6bd4\u4e03\u5206\u949f\u4e00\u5f20\u5bb9\u6613\u63a5\u53d7\u5f97\u591a\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004928-6aa1fe98e0d56.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u2003\u2003\u4e0d\u8fc7&#xff0c;\u8fd9\u7ec4\u672c\u5730\u6570\u636e\u53ea\u6709\u4e00\u7ec4\u914d\u5bf9\u6837\u672c\u3002Base \u5355\u5f20\u9700\u8981\u4e03\u5206\u949f\u4ee5\u4e0a&#xff0c;\u6240\u4ee5\u8fd9\u91cc\u4f18\u5148\u9a8c\u8bc1\u8def\u5f84\u80fd\u5426\u8dd1\u901a&#xff0c;\u6ca1\u6709\u5c55\u5f00\u5b8c\u6574\u7684\u591a\u63d0\u793a\u8bcd\u3001\u591a\u968f\u673a\u79cd\u5b50\u6d4b\u8bd5\u30029.12\u00d7 \u5e94\u5f53\u4f5c\u4e3a\u8fd9\u6b21\u8fd0\u884c\u7684\u7ed3\u679c&#xff0c;\u800c\u4e0d\u662f\u6240\u6709\u672c\u5730\u4efb\u52a1\u7684\u5e73\u5747\u52a0\u901f\u6bd4\u3002\u6587\u5b57\u8868\u73b0\u4e5f\u6ca1\u6709\u597d\u5230\u53ef\u4ee5\u8df3\u8fc7\u68c0\u67e5\u3002RapidOCR \u5728 LoRA-8 \u6837\u672c\u4e2d\u57fa\u672c\u8bc6\u522b\u51fa\u4e86\u6807\u9898 LOCALAI \u548c GPU&#xff0c;\u4f46\u5c06 MODEL \u8bc6\u522b\u4e3a MOOFL&#xff0c;IMAGE \u5219\u672a\u68c0\u51fa\u3002\u4e0e Base \u6837\u672c\u76f8\u6bd4&#xff0c;\u53ef\u4ee5\u89c2\u5bdf\u5230\u5c40\u90e8\u6587\u5b57\u95ee\u9898\u3002\u4e00\u4e2a\u6837\u672c\u4e0d\u8db3\u4ee5\u5224\u65ad LoRA \u662f\u5426\u4f1a\u7a33\u5b9a\u964d\u4f4e\u6587\u5b57\u8d28\u91cf&#xff0c;\u4e5f\u4e0d\u80fd\u76f4\u63a5\u628a\u5dee\u5f02\u5f52\u56e0\u4e8e\u5378\u8f7d\u8def\u5f84\u3002\u5b9e\u9645\u4f7f\u7528\u65f6&#xff0c;\u6211\u4f1a\u5148\u7528\u5c11\u91cf\u77ed\u6587\u5b57\u9a8c\u8bc1\u6548\u679c&#xff1b;\u9700\u8981\u51c6\u786e\u5448\u73b0\u5927\u91cf\u6587\u5b57\u7684\u56fe\u50cf&#xff0c;\u4ecd\u8981\u9010\u5f20\u68c0\u67e5\u3002<\/p>\n<h2>2. A100 \u5b9e\u6d4b&#xff1a;\u63a8\u7406\u901f\u5ea6\u4e0e\u751f\u6210\u8d28\u91cf<\/h2>\n<h3>2.1 \u4e0d\u540c\u4efb\u52a1\u7684\u52a0\u901f\u6548\u679c<\/h3>\n<p>\u2003\u2003\u672c\u5730\u8dd1\u901a\u540e&#xff0c;\u6211\u5c06\u540c\u4e00\u4efd LoRA \u6743\u91cd\u653e\u5230 A100 \u4e0a&#xff0c;\u8865\u505a\u4e86\u6587\u751f\u56fe\u3001\u4e2d\u6587\u4fe1\u606f\u56fe\u548c\u56fe\u50cf\u7f16\u8f91\u6d4b\u8bd5\u3002\u6587\u751f\u56fe\u4f7f\u7528 3 \u6761\u63d0\u793a\u8bcd\u30013 \u4e2a\u968f\u673a\u79cd\u5b50&#xff0c;\u5171 9 \u5f20\u56fe\u8ba1\u7b97\u5e73\u5747\u8017\u65f6\u3002<\/p>\n<table>\n<tr>\u4efb\u52a1Base-50LoRA-8\u52a0\u901f\u6bd4<\/tr>\n<tbody>\n<tr>\n<td>\u6587\u751f\u56fe&#xff0c;9 \u5f20\u5747\u503c&#xff0c;1024\u00d71024<\/td>\n<td>16.616s<\/td>\n<td>1.433s<\/td>\n<td>11.6\u00d7<\/td>\n<\/tr>\n<tr>\n<td>\u4e2d\u6587\u4fe1\u606f\u56fe&#xff0c;1536\u00d72720<\/td>\n<td>56.049s<\/td>\n<td>5.598s<\/td>\n<td>10.0\u00d7<\/td>\n<\/tr>\n<tr>\n<td>\u56fe\u50cf\u7f16\u8f91&#xff0c;8 \u4e2a\u6837\u4f8b\u5747\u503c&#xff0c;fast \u6a21\u5f0f<\/td>\n<td>69.513s<\/td>\n<td>26.230s<\/td>\n<td>2.65\u00d7<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u2003\u2003A100 \u4e0a\u7684 LoRA-8 \u6587\u751f\u56fe\u914d\u7f6e\u5982\u4e0b&#xff1a;<\/p>\n<p>python examples\/t2i\/inference.py <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;model_path<\/span> \/root\/autodl-tmp\/SenseNova-U1.5-8B-MoT <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;lora_path<\/span> \/root\/autodl-tmp\/SenseNova-U1.5-8B-MoT-LoRAs\/SenseNova-U1.5-8B-MoT-LoRA-8step.safetensors <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;vram_mode<\/span> full <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;cfg_scale<\/span> <span class=\"token number\">1.0<\/span> <span class=\"token parameter variable\">&#8211;num_steps<\/span> <span class=\"token number\">8<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;width<\/span> <span class=\"token number\">1024<\/span> <span class=\"token parameter variable\">&#8211;height<\/span> <span class=\"token number\">1024<\/span> <span class=\"token parameter variable\">&#8211;seed<\/span> <span class=\"token number\">42<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;output<\/span> outputs\/lora8\/0001_A_1024x1024.png<\/p>\n<p>\u2003\u2003\u4e0b\u9762\u662f\u540c\u4e00\u6761\u4e2d\u6587\u4fe1\u606f\u56fe\u63d0\u793a\u8bcd\u3001\u540c\u4e00\u968f\u673a\u79cd\u5b50\u7684\u8f93\u51fa\u5bf9\u6bd4\u3002\u8868\u4e2d\u7684\u65f6\u95f4\u4e3a\u5bf9\u5e94\u914d\u7f6e\u7684\u6587\u751f\u56fe\u5747\u503c&#xff0c;\u5e76\u975e\u8fd9\u4e24\u5f20\u56fe\u5355\u72ec\u7684\u8ba1\u65f6\u7ed3\u679c\u3002<\/p>\n<table>\n<tr>Base-50LoRA-8<\/tr>\n<tbody>\n<tr>\n<td><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004929-6aa1fe9926748.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/td>\n<td><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004930-6aa1fe9a2f99d.png\" alt=\"\u56fe\u7247\" \/><\/td>\n<\/tr>\n<tr>\n<td>50 \u6b65&#xff0c;CFG 4.0&#xff1b;\u6587\u751f\u56fe\u5e73\u5747 16.616s\/\u5f20<\/td>\n<td>8 \u6b65&#xff0c;CFG 1.0&#xff1b;\u6587\u751f\u56fe\u5e73\u5747 1.433s\/\u5f20<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u2003\u2003\u7f16\u8f91\u4efb\u52a1\u7684\u52a0\u901f\u6bd4\u660e\u663e\u4f4e\u4e8e\u6587\u751f\u56fe\u3002\u5b83\u9664\u4e86\u751f\u6210&#xff0c;\u8fd8\u8981\u5904\u7406\u8f93\u5165\u56fe\u50cf\u548c\u7f16\u8f91\u6307\u4ee4&#xff1b;\u51cf\u5c11\u53bb\u566a\u6b65\u6570\u5e76\u4e0d\u4f1a\u7b49\u6bd4\u4f8b\u7f29\u77ed\u6240\u6709\u73af\u8282\u3002\u56e0\u6b64&#xff0c;\u6587\u751f\u56fe\u7684 11.6\u00d7 \u4e0d\u80fd\u76f4\u63a5\u5957\u7528\u5230\u7f16\u8f91\u4efb\u52a1\u4e0a\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004930-6aa1fe9aace6d.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u2003\u2003\u7f16\u8f91\u8fc7\u7a0b\u4e2d\u8fd8\u9047\u5230\u4e86\u53e6\u4e00\u5904 OOM&#xff1a;A100 40GB \u5728 full \u6a21\u5f0f\u4e0b\u4e5f\u66fe\u65e0\u6cd5\u7ee7\u7eed\u5206\u914d 1.10 GiB \u663e\u5b58\u3002\u76f8\u5173\u7406\u89e3\u5206\u652f\u4f7f\u7528 eager attention&#xff0c;\u9ad8\u5206\u8fa8\u7387\u8f93\u5165\u5e26\u6765\u7684\u5f00\u9500\u53e0\u52a0\u6743\u91cd\u5360\u7528&#xff0c;\u8d85\u51fa\u4e86\u5f53\u65f6\u7684\u53ef\u7528\u663e\u5b58\u3002\u6240\u4ee5&#xff0c;\u80fd\u5b8c\u6574\u653e\u4e0b\u6743\u91cd&#xff0c;\u4e0d\u4ee3\u8868\u6240\u6709\u4efb\u52a1\u90fd\u80fd\u4f7f\u7528 full\u3002\u8fd9\u4e5f\u662f\u7f16\u8f91\u6d4b\u8bd5\u6539\u7528 fast \u6a21\u5f0f\u7684\u539f\u56e0\u3002<\/p>\n<h3>2.2 \u6587\u5b57\u8d28\u91cf\u4e0e\u7ea6\u675f\u9075\u5faa<\/h3>\n<p>\u2003\u2003\u751f\u6210\u5feb\u4e86\u591a\u5c11\u5bb9\u6613\u8ba1\u65f6&#xff0c;\u8d28\u91cf\u6709\u6ca1\u6709\u53d8\u5316\u5219\u9700\u8981\u5177\u4f53\u68c0\u67e5\u3002\u6211\u91c7\u7528\u4e86\u4e24\u79cd\u65b9\u5f0f&#xff1a;\u7528 OCR \u68c0\u67e5\u6307\u5b9a\u6587\u5b57\u662f\u5426\u51fa\u73b0&#xff0c;\u518d\u4eba\u5de5\u6838\u5bf9\u5e03\u5c40\u3001\u989c\u8272\u3001\u6570\u91cf\u548c\u7981\u6b62\u9879\u7b49\u8981\u6c42\u3002\u5728 22 \u5f20\u56fe\u3001228 \u4e2a\u68c0\u67e5\u6761\u76ee\u4e2d&#xff0c;\u539f\u59cb OCR \u6587\u5b57\u53ec\u56de\u7387\u4e3a&#xff1a;<\/p>\n<table>\n<tr>\u914d\u7f6e\u6307\u5b9a\u6587\u672c\u53ec\u56de\u7387<\/tr>\n<tbody>\n<tr>\n<td>Base-50<\/td>\n<td>94.7%<\/td>\n<\/tr>\n<tr>\n<td>LoRA-8<\/td>\n<td>95.6%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u2003\u2003\u8fd9\u4e9b\u6570\u5b57\u6ca1\u6709\u8fdb\u884c\u4eba\u5de5\u4fee\u6b63\u3002RapidOCR \u5bf9\u5c0f\u5b57\u548c\u8868\u683c\u5b58\u5728\u6f0f\u68c0\u3001\u8bef\u8bfb&#xff0c;\u56e0\u6b64\u7ed3\u679c\u4f1a\u53d7\u5230\u8bc6\u522b\u5668\u672c\u8eab\u7684\u5f71\u54cd&#xff0c;\u4e0d\u80fd\u76f4\u63a5\u5f53\u4f5c\u56fe\u50cf\u4e2d\u6587\u5b57\u51c6\u786e\u7387\u7684\u5b8c\u6574\u8bc4\u4ef7\u3002 \u2003\u2003\u4eba\u5de5\u8bc4\u5206\u91c7\u7528\u4e09\u6863\u5206\u503c&#xff1a;\u5b8c\u5168\u9075\u5faa\u8bb0 1 \u5206&#xff0c;\u90e8\u5206\u9075\u5faa\u8bb0 0.5 \u5206&#xff0c;\u672a\u9075\u5faa\u8bb0 0 \u5206&#xff1b;\u65e0\u6cd5\u5224\u65ad\u7684\u6761\u76ee\u5355\u72ec\u6807\u8bb0\u3002<\/p>\n<table>\n<tr>\u4efb\u52a1Base-50LoRA-8<\/tr>\n<tbody>\n<tr>\n<td>\u6587\u751f\u56fe&#xff0c;\u5404 54 \u6761\u76ee<\/td>\n<td>93.52%<\/td>\n<td>95.37%<\/td>\n<\/tr>\n<tr>\n<td>\u7f16\u8f91&#xff0c;\u5404 8 \u6761\u76ee<\/td>\n<td>100%<\/td>\n<td>100%<\/td>\n<\/tr>\n<tr>\n<td>\u4fe1\u606f\u56fe&#xff0c;\u5404 8 \u6761\u76ee<\/td>\n<td>68.75%<\/td>\n<td>81.25%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u2003\u2003\u5728\u8fd9\u51e0\u7ec4\u6837\u672c\u4e2d&#xff0c;LoRA-8 \u7684\u4e24\u9879\u8bc4\u5206\u90fd\u6ca1\u6709\u4f4e\u4e8e Base-50\u3002\u4e0d\u8fc7&#xff0c;\u7f16\u8f91\u4efb\u52a1\u53ea\u6709 8 \u4e2a\u68c0\u67e5\u6761\u76ee&#xff0c;\u4fe1\u606f\u56fe\u4e5f\u6ca1\u6709\u9010\u9879\u505a\u5230\u51c6\u786e&#xff0c;\u4e0d\u80fd\u5c06\u8fd9\u4e9b\u5206\u6570\u6982\u62ec\u4e3a\u201c\u52a0\u901f\u5b8c\u5168\u6ca1\u6709\u8d28\u91cf\u4ee3\u4ef7\u201d\u3002\u540e\u9762\u7684\u957f\u6307\u4ee4\u6d4b\u8bd5&#xff0c;\u5c31\u51fa\u73b0\u4e86\u4e0d\u540c\u7ed3\u679c\u3002\u4e00\u4e2a\u6bd4\u8f83\u76f4\u89c2\u7684\u6848\u4f8b\u662f\u5b98\u65b9\u4e2d\u6587\u4fe1\u606f\u56fe\u63d0\u793a\u8bcd\u201c\u65b0\u5458\u5de5\u7b2c\u4e00\u5468\u751f\u5b58\u624b\u518c\u201d&#xff0c;\u8f93\u51fa\u5c3a\u5bf8\u4e3a 1536\u00d72720\u3002\u4e24\u79cd\u914d\u7f6e\u90fd\u751f\u6210\u4e86\u7eb5\u5411\u4fe1\u606f\u56fe&#xff0c;\u5305\u542b\u6807\u9898\u3001\u5206\u65e5\u65f6\u95f4\u8f74\u548c\u6a21\u5757\u5361\u7247\u3002Base-50 \u7684\u6307\u5b9a\u6587\u672c\u53ec\u56de\u4e3a 9\/11&#xff0c;\u7f3a\u5c11\u201c\u7b2c\u4e00\u5468\u539f\u5219\u201d\u548c\u5468\u4e94\u65f6\u95f4\u8f74&#xff1b;LoRA-8 \u4e3a 11\/11&#xff0c;\u8f93\u51fa\u4e2d\u6709 45 \u884c\u53ef\u8bfb\u4e2d\u6587\u3002\u4eba\u5de5\u68c0\u67e5\u4e5f\u5bf9\u5e94\u53d1\u73b0\u4e86\u8fd9\u4e24\u4e2a\u533a\u5757\u7684\u5dee\u5f02\u3002\u8fd9\u4e00\u5f20\u56fe\u4e0a&#xff0c;LoRA-8 \u4e0d\u4ec5\u7528\u65f6\u66f4\u77ed&#xff0c;\u5185\u5bb9\u8fd8\u66f4\u5b8c\u6574\u3002\u5b83\u4e0e\u672c\u5730\u5c0f\u5b57\u6837\u672c\u7684\u8868\u73b0\u6709\u660e\u663e\u533a\u522b&#xff0c;\u4f46\u73af\u5883\u3001\u5206\u8fa8\u7387\u548c\u63d0\u793a\u8bcd\u90fd\u53d1\u751f\u4e86\u53d8\u5316&#xff0c;\u4e0d\u80fd\u5c06\u6587\u5b57\u6548\u679c\u7684\u6539\u5584\u76f4\u63a5\u5f52\u529f\u4e8e A100\u3002\u80fd\u786e\u8ba4\u7684\u662f&#xff0c;\u6a21\u578b\u5728\u8fd9\u7ec4\u9ad8\u5206\u8fa8\u7387\u4fe1\u606f\u56fe\u4e2d\u53ef\u4ee5\u751f\u6210\u5927\u6bb5\u53ef\u8bfb\u4e2d\u6587&#xff0c;\u672c\u5730\u67d0\u5f20\u56fe\u7684\u5c0f\u5b57\u5931\u8d25\u5e76\u4e0d\u4ee3\u8868\u6240\u6709\u573a\u666f\u90fd\u4f1a\u5982\u6b64\u3002 \u2003 \u2003\u2003\u8bc4\u6d4b\u811a\u672c\u8fd0\u884c\u5728\u72ec\u7acb\u7684 .venv-eval \u73af\u5883\u4e2d&#xff1a;<\/p>\n<p>python scripts\/run_ocr_eval.py<br \/>\n<span class=\"token comment\"># -&gt; results\/ocr\/summary.json<\/span><\/p>\n<p>python scripts\/summarize_results.py<br \/>\n<span class=\"token comment\"># -&gt; results\/scoring\/summary-human.json<\/span><\/p>\n<h3>2.3 \u5206\u8fa8\u7387\u6d4b\u8bd5&#xff1a;4.2MP \u4e0e UHD<\/h3>\n<p>\u2003\u2003\u9664\u4e86\u4e2d\u6587\u4fe1\u606f\u56fe&#xff0c;\u6211\u8fd8\u7528\u63d0\u793a\u8bcd A \u548c\u4e09\u4e2a\u968f\u673a\u79cd\u5b50&#xff08;42\u3001123\u30012026&#xff09;&#xff0c;\u6d4b\u8bd5\u4e86\u4e24\u79cd\u7ea6 4.2MP \u7684\u5206\u8fa8\u7387&#xff1a;<\/p>\n<table>\n<tr>\u5206\u8fa8\u7387\u6d4b\u8bd5\u6b21\u6570\u8017\u65f6\u7ed3\u679c<\/tr>\n<tbody>\n<tr>\n<td>1024\u00d71024&#xff0c;\u5bf9\u7167\u57fa\u7ebf<\/td>\n<td>3<\/td>\n<td>\u5e73\u5747 1.433s<\/td>\n<td>\u4f5c\u4e3a\u5bf9\u7167<\/td>\n<\/tr>\n<tr>\n<td>2048\u00d72048<\/td>\n<td>3<\/td>\n<td>\u4e0e\u4e0b\u4e00\u7ec4\u5408\u5e76\u5747\u503c\u4e3a 4.840s<\/td>\n<td>3\/3 \u6210\u529f<\/td>\n<\/tr>\n<tr>\n<td>2720\u00d71536<\/td>\n<td>3<\/td>\n<td>\u540c\u4e0a<\/td>\n<td>3\/3 \u6210\u529f<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u2003\u2003\u4e24\u4e2a\u9ad8\u5206\u8fa8\u7387\u914d\u7f6e\u5171\u516d\u6b21\u8fd0\u884c\u5168\u90e8\u6210\u529f&#xff0c;\u6ca1\u6709\u51fa\u73b0\u5206\u8fa8\u7387\u8b66\u544a&#xff0c;\u5cf0\u503c GPU allocated \u4e3a 34.02 GiB\u3002\u5728\u8fd9\u7ec4\u4efb\u52a1\u4e2d&#xff0c;\u76f8\u6bd4\u7ea6 33 GiB \u7684\u6743\u91cd\u5360\u7528&#xff0c;\u63d0\u9ad8\u5206\u8fa8\u7387\u5e26\u6765\u7684\u989d\u5916\u663e\u5b58\u5f00\u9500\u76f8\u5bf9\u6709\u9650\u3002\u7ee7\u7eed\u6d4b\u8bd5 UHD \u5c3a\u5bf8\u65f6&#xff0c;3840\u00d72160 \u89e6\u53d1\u4e86\u5c3a\u5bf8\u6821\u9a8c\u5931\u8d25\u3002\u5c06\u9ad8\u5ea6\u8c03\u6574\u4e3a 2144 \u540e&#xff0c;3840\u00d72144 \u6210\u529f\u751f\u6210&#xff0c;\u8017\u65f6 10.70 \u79d2\u3002\u8fd9\u91cc\u8981\u533a\u5206\u5c3a\u5bf8\u6821\u9a8c\u548c\u751f\u6210\u80fd\u529b&#xff1a;\u67d0\u4e2a\u5c3a\u5bf8\u672a\u901a\u8fc7\u68c0\u67e5&#xff0c;\u4e0d\u7b49\u4e8e\u6a21\u578b\u65e0\u6cd5\u751f\u6210\u63a5\u8fd1\u8be5\u50cf\u7d20\u6570\u7684\u56fe\u50cf\u3002\u540c\u6837&#xff0c;\u4e00\u6b21\u8d85\u89c4\u683c\u751f\u6210\u6210\u529f&#xff0c;\u4e5f\u4e0d\u80fd\u8bf4\u660e\u5b83\u5df2\u7ecf\u9002\u5408\u7a33\u5b9a\u6279\u91cf\u4f7f\u7528\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004931-6aa1fe9b5babb.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h3>2.4 \u957f\u6307\u4ee4\u6d4b\u8bd5&#xff1a;\u7ec6\u7c92\u5ea6\u7ea6\u675f\u7684\u6267\u884c\u60c5\u51b5<\/h3>\n<p>\u2003\u2003\u4fe1\u606f\u56fe\u5e38\u5e38\u9700\u8981\u4e00\u6b21\u5199\u5165\u5f88\u591a\u8981\u6c42\u3002\u4e3a\u4e86\u89c2\u5bdf\u6307\u4ee4\u53d8\u957f\u540e\u7684\u8868\u73b0&#xff0c;\u6211\u6784\u9020\u4e86\u56db\u7ea7\u201c\u667a\u80fd\u5bb6\u5c45\u5165\u95e8\u6307\u5357\u201d\u63d0\u793a\u8bcd\u3002\u6bcf\u4e00\u7ea7\u4fdd\u7559\u4e0a\u4e00\u7ea7\u7684\u8981\u6c42&#xff0c;\u518d\u8ffd\u52a0\u65b0\u7ea6\u675f&#xff0c;\u907f\u514d\u76f4\u63a5\u62ff\u5185\u5bb9\u6beb\u4e0d\u76f8\u5173\u7684\u957f\u77ed\u63d0\u793a\u8bcd\u4f5c\u6bd4\u8f83\u3002<\/p>\n<table>\n<tr>\u6d4b\u8bd5\u7f16\u53f7\u5b57\u7b26\u6570Token \u6570\u65b0\u589e\u7ea6\u675f<\/tr>\n<tbody>\n<tr>\n<td>P200<\/td>\n<td>161<\/td>\n<td>106<\/td>\n<td>8<\/td>\n<\/tr>\n<tr>\n<td>P1000<\/td>\n<td>492<\/td>\n<td>334<\/td>\n<td>&#043;12<\/td>\n<\/tr>\n<tr>\n<td>P2000<\/td>\n<td>922<\/td>\n<td>619<\/td>\n<td>&#043;10<\/td>\n<\/tr>\n<tr>\n<td>P4000<\/td>\n<td>3,104<\/td>\n<td>2,076<\/td>\n<td>&#043;40<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u2003\u2003\u8fd9\u91cc\u7684 P200\u3001P1000 \u7b49\u662f\u6d4b\u8bd5\u7f16\u53f7&#xff0c;\u5b9e\u9645\u957f\u5ea6\u4ee5\u5b57\u7b26\u6570\u5217\u4e3a\u51c6\u3002\u5d4c\u5957\u8bbe\u8ba1\u65b9\u4fbf\u8ffd\u8e2a\u8981\u6c42\u7684\u53d8\u5316&#xff0c;\u4f46\u65b0\u589e\u5185\u5bb9\u4ecd\u53ef\u80fd\u5f71\u54cd\u539f\u6709\u8981\u6c42&#xff0c;\u56e0\u6b64\u5b83\u4e5f\u4e0d\u80fd\u5b8c\u5168\u5206\u79bb\u201c\u957f\u5ea6\u201d\u548c\u201c\u4efb\u52a1\u96be\u5ea6\u201d\u3002<\/p>\n<p>\u2003\u2003\u6d4b\u8bd5\u7ed3\u679c\u5982\u4e0b&#xff1a;<\/p>\n<table>\n<tr>\u68c0\u67e5\u5185\u5bb9\u7ed3\u679c<\/tr>\n<tbody>\n<tr>\n<td>LoRA-8 \u751f\u6210\u8017\u65f6<\/td>\n<td>P200 \u4e3a 5.58s&#xff0c;P4000 \u4e3a 5.44s<\/td>\n<\/tr>\n<tr>\n<td>P4000 \u6307\u5b9a\u6587\u672c OCR \u53ec\u56de<\/td>\n<td>Base-50 \u4e3a 95.3%&#xff0c;LoRA-8 \u4e3a 93.0%<\/td>\n<\/tr>\n<tr>\n<td>\u4eba\u5de5\u7ea6\u675f\u68c0\u67e5\u6c47\u603b<\/td>\n<td>Base-50 \u4e3a 77.2%&#xff0c;LoRA-8 \u4e3a 72.1%<\/td>\n<\/tr>\n<tr>\n<td>\u5404\u7ea7\u4eba\u5de5\u8bc4\u5206&#xff0c;Base \/ LoRA<\/td>\n<td>P200&#xff1a;87.5% \/ 87.5%&#xff1b;P1000&#xff1a;100% \/ 100%&#xff1b;P2000&#xff1a;70.0% \/ 65.0%&#xff1b;P4000&#xff1a;77.9% \/ 71.2%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004931-6aa1fe9b98a41.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004931-6aa1fe9bc7980.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u2003\u2003\u8017\u65f6\u6ca1\u6709\u968f\u7740\u63d0\u793a\u8bcd\u957f\u5ea6\u660e\u663e\u589e\u957f&#xff0c;\u4f46\u7ea6\u675f\u9075\u5faa\u5e76\u6ca1\u6709\u4e00\u76f4\u4fdd\u6301\u3002\u8fd9\u7ec4\u957f\u6307\u4ee4\u4efb\u52a1\u4e2d&#xff0c;LoRA-8 \u7684\u6c47\u603b\u8bc4\u5206\u4f4e\u4e8e Base-50&#xff0c;\u4e5f\u8bf4\u660e\u524d\u9762\u7684\u8d28\u91cf\u7ed3\u8bba\u4e0d\u80fd\u8de8\u4efb\u52a1\u76f4\u63a5\u6cbf\u7528\u3002<\/p>\n<p>\u2003\u2003\u9010\u9879\u68c0\u67e5\u540e&#xff0c;\u9519\u8bef\u4e3b\u8981\u96c6\u4e2d\u5728\u8868\u683c\u5217\u7ed3\u6784\u3001\u7cbe\u786e\u6570\u91cf\u548c\u6982\u5ff5\u4e0e\u6587\u672c\u7684\u5bf9\u5e94\u5173\u7cfb\u3002\u4f8b\u5982&#xff0c;\u672c\u6765\u8981\u6c42\u4e09\u5217\u7684\u8868\u683c\u53d8\u6210\u4e24\u5217&#xff0c;\u56fe\u6807\u6570\u91cf\u4e0d\u7b26\u5408\u8981\u6c42&#xff0c;\u6216\u8005\u6587\u6848\u51fa\u73b0\u5728\u9519\u8bef\u7684\u6a21\u5757\u4e2d\u3002\u76f8\u6bd4\u4e4b\u4e0b&#xff0c;\u914d\u8272\u548c\u6574\u4f53\u6392\u7248\u66f4\u5bb9\u6613\u6ee1\u8db3\u3002<\/p>\n<p>\u2003\u2003\u5176\u4e2d\u4e00\u7ec4\u9519\u8bef\u5f88\u5178\u578b&#xff1a;Base \u548c LoRA \u90fd\u5728\u201c\u667a\u80fd\u7a97\u5e18\u201d\u6a21\u5757\u4fdd\u7559\u4e86\u7a97\u5e18\u56fe\u6807&#xff0c;\u5374\u586b\u5165\u201c\u73af\u5883\u76d1\u6d4b\u201d\u7684\u6587\u6848\u3002\u6587\u5b57\u672c\u8eab\u53ef\u80fd\u8bfb\u5f97\u51fa\u6765&#xff0c;\u4f46\u653e\u9519\u4e86\u4f4d\u7f6e&#xff0c;OCR \u53ec\u56de\u672a\u5fc5\u80fd\u5145\u5206\u53cd\u6620\u8fd9\u7c7b\u95ee\u9898\u3002\u4e24\u79cd\u914d\u7f6e\u51fa\u73b0\u76f8\u4f3c\u9519\u8bef&#xff0c;\u503c\u5f97\u7ee7\u7eed\u7528\u66f4\u591a\u968f\u673a\u79cd\u5b50\u590d\u6d4b&#xff1b;\u73b0\u6709\u6837\u672c\u8fd8\u4e0d\u8db3\u4ee5\u5c06\u5176\u8ba4\u5b9a\u4e3a\u7a33\u5b9a\u7684\u6a21\u578b\u7f3a\u9677\u3002\u4f46\u5bf9\u5b9e\u9645\u5199\u63d0\u793a\u8bcd\u5df2\u7ecf\u6709\u542f\u53d1&#xff1a;\u76f8\u90bb\u6a21\u5757\u7684\u8981\u6c42\u8981\u5c3d\u91cf\u5206\u6e05\u695a&#xff0c;\u5c24\u5176\u662f\u201c\u54ea\u4e2a\u56fe\u6807\u5bf9\u5e94\u54ea\u6bb5\u6587\u5b57\u201d\u3002\u5bf9\u4e8e\u5305\u542b\u51e0\u5341\u9879\u7ec6\u8282\u8981\u6c42\u7684\u4fe1\u606f\u56fe&#xff0c;\u6211\u66f4\u503e\u5411\u4e8e\u5148\u62c6\u6210\u51e0\u5f20\u5c0f\u56fe&#xff0c;\u518d\u68c0\u67e5\u5404\u81ea\u7684\u5185\u5bb9\u3002\u6bcf\u5f20\u5148\u63a7\u5236\u5728\u7ea6 20 \u9879\u7ea6\u675f\u4ee5\u5185&#xff0c;\u53ef\u4ee5\u4f5c\u4e3a\u8d77\u6b65\u65b9\u6848&#xff0c;\u4f46\u8fd9\u53ea\u662f\u6839\u636e\u672c\u6b21\u9519\u8bef\u5206\u5e03\u63d0\u51fa\u7684\u5c1d\u8bd5\u65b9\u5411&#xff0c;\u5e76\u4e0d\u662f\u6a21\u578b\u7684\u786c\u4e0a\u9650\u3002<\/p>\n<h2>3. \u5f02\u5e38\u8f93\u51fa\u6392\u67e5&#xff1a;\u4e00\u6b21\u672a\u590d\u73b0\u7684\u5168\u9ed1\u56fe\u50cf<\/h2>\n<p>\u2003\u2003\u9664 OOM \u5916&#xff0c;\u7f16\u8f91\u4efb\u52a1\u8fd8\u51fa\u73b0\u8fc7\u4e00\u6b21\u66f4\u5bb9\u6613\u6f0f\u6389\u7684\u5931\u8d25&#xff1a;\u5f00\u542f &#8211;think \u540e&#xff0c;\u63a8\u7406\u6587\u672c\u6b63\u5e38\u7ed3\u675f&#xff0c;\u8f93\u51fa\u5374\u662f\u4e00\u5f20\u5168\u9ed1\u56fe\u3002\u8fd9\u5f20\u56fe\u5c3a\u5bf8\u4e3a 2048\u00d72048&#xff0c;\u50cf\u7d20\u5747\u503c\u4e3a 0&#xff0c;\u53ea\u6709\u4e00\u79cd\u989c\u8272&#xff0c;\u6587\u4ef6\u5927\u5c0f\u7ea6 12KB\u3002\u540c\u4e00\u4efb\u52a1\u4e0d\u5f00\u542f &#8211;think \u65f6&#xff0c;\u8f93\u51fa\u6b63\u5e38\u3002\u5982\u679c\u53ea\u68c0\u67e5\u65e5\u5fd7\u662f\u5426\u62a5\u9519&#xff0c;\u5f88\u5bb9\u6613\u628a\u8fd9\u6b21\u8fd0\u884c\u8bb0\u6210\u6210\u529f\u3002\u6211\u6309\u539f\u914d\u7f6e\u91cd\u8dd1\u4e86\u5b98\u65b9\u7f16\u8f91\u6837\u4f8b 6&#xff0c;\u5c06\u201cWARFIGHTER\u201d\u66ff\u6362\u6210\u201cBATTLEFIELD\u201d&#xff1a;<\/p>\n<p>python examples\/editing\/inference.py <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;model_path<\/span> \/root\/autodl-tmp\/SenseNova-U1.5-8B-MoT <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;prompt<\/span> <span class=\"token string\">&#034;Replace the text WARFIGHTER with BATTLEFIELD.&#034;<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;image<\/span> \/root\/autodl-tmp\/data\/editing\/6.webp <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;vram_mode<\/span> fast <span class=\"token parameter variable\">&#8211;dtype<\/span> bfloat16 <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;cfg_scale<\/span> <span class=\"token number\">4.0<\/span> <span class=\"token parameter variable\">&#8211;cfg_norm<\/span> none <span class=\"token parameter variable\">&#8211;num_steps<\/span> <span class=\"token number\">50<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;seed<\/span> <span class=\"token number\">42<\/span> <span class=\"token parameter variable\">&#8211;think<\/span> <span class=\"token punctuation\">\\\\<\/span><br \/>\n  <span class=\"token parameter variable\">&#8211;output<\/span> outputs\/think-pair\/think-retry.png<\/p>\n<p>\u2003\u2003\u8fd9\u6b21\u6ca1\u6709\u590d\u73b0\u3002\u91cd\u8dd1\u56fe\u50cf\u5305\u542b 180,080 \u79cd\u989c\u8272&#xff0c;\u6587\u4ef6\u7ea6 5.43MB&#xff0c;\u4e0e\u4e0d\u5f00\u542f &#8211;think \u7684\u7ed3\u679c\u76ee\u89c6\u63a5\u8fd1\u3002<\/p>\n<table>\n<tr>\u5f00\u542f think \u540e\u91cd\u8dd1\u4e0d\u5f00\u542f think\u6700\u521d\u7684\u5168\u9ed1\u8f93\u51fa<\/tr>\n<tbody>\n<tr>\n<td><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004932-6aa1fe9c26ab3.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/td>\n<td><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004934-6aa1fe9e6fd9a.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/td>\n<td><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260910004936-6aa1fea0c917d.png\" alt=\"\u56fe\u7247\" \/><\/td>\n<\/tr>\n<tr>\n<td>think-retry.png<\/td>\n<td>nothink.png<\/td>\n<td>think.png<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u2003\u2003\u6e90\u7801\u4e2d\u6709\u4e00\u6bb5\u9700\u8981\u8fdb\u4e00\u6b65\u68c0\u67e5&#xff1a;cfg_norm&#061;&#039;none&#039; \u65f6&#xff0c;CFG \u4f7f\u7528\u4ee5\u4e0b\u7ebf\u6027\u5916\u63a8&#xff1a;<\/p>\n<p>v_pred <span class=\"token operator\">&#061;<\/span> out_img_cond <span class=\"token operator\">&#043;<\/span> cfg_scale <span class=\"token operator\">*<\/span> <span class=\"token punctuation\">(<\/span>out_cond <span class=\"token operator\">&#8211;<\/span> out_img_cond<span class=\"token punctuation\">)<\/span><\/p>\n<p>\u2003\u2003\u5982\u679c\u4e2d\u95f4\u5f20\u91cf\u5df2\u7ecf\u51fa\u73b0\u975e\u6709\u9650\u503c&#xff0c;\u540e\u7eed\u7684 clamp(0,1) \u65e0\u6cd5\u6d88\u9664 NaN&#xff0c;\u56fe\u50cf\u8f6c\u6362\u9636\u6bb5\u53ef\u80fd\u7ee7\u7eed\u4ea7\u751f\u5f02\u5e38\u8f93\u51fa\u3002\u8fd9\u4e2a\u8def\u5f84\u4e3a\u6392\u67e5\u63d0\u4f9b\u4e86\u65b9\u5411&#xff0c;\u4f46\u76ee\u524d\u6ca1\u6709\u6355\u83b7\u539f\u59cb\u5931\u8d25\u65f6\u7684\u4e2d\u95f4\u5f20\u91cf&#xff0c;\u4e0d\u80fd\u786e\u8ba4\u95ee\u9898\u5c31\u662f\u7531 BF16 \u4e0b\u7684 CFG \u5916\u63a8\u5f15\u8d77\u3002\u4e0b\u4e00\u6b65\u5e94\u5728 CFG \u524d\u540e\u53ca\u89e3\u7801\u9636\u6bb5\u68c0\u67e5\u5f20\u91cf\u662f\u5426\u5305\u542b NaN \u6216 Inf&#xff0c;\u800c\u4e0d\u662f\u4ec5\u51ed\u5168\u9ed1\u7ed3\u679c\u5012\u63a8\u539f\u56e0\u3002\u540c\u6837\u7684\u968f\u673a\u79cd\u5b50\u4e5f\u4e0d\u8db3\u4ee5\u89e3\u91ca\u4e3a\u4ec0\u4e48\u4e24\u6b21\u8fd0\u884c\u8868\u73b0\u4e0d\u540c\u3002\u8017\u65f6\u65b9\u9762&#xff0c;\u8fd9\u4e2a\u7f16\u8f91\u6837\u4f8b\u5f00\u542f &#8211;think \u540e\u7ea6\u4e3a\u4e0d\u5f00\u542f\u65f6\u7684 3.1 \u500d&#xff1b;\u672c\u5730\u6587\u751f\u56fe\u914d\u5bf9\u4e2d\u4e5f\u8bb0\u5f55\u8fc7\u7ea6 2.84 \u500d\u7684\u5f00\u9500\u3002\u56e0\u6b64&#xff0c;\u6211\u4e0d\u4f1a\u9ed8\u8ba4\u7ed9\u6240\u6709\u4efb\u52a1\u6253\u5f00\u5b83&#xff0c;\u800c\u4f1a\u5148\u68c0\u67e5\u5177\u4f53\u4efb\u52a1\u662f\u5426\u771f\u7684\u53d7\u76ca\u3002\u8fd9\u6b21\u5931\u8d25\u5e26\u6765\u7684\u76f4\u63a5\u63d0\u9192\u662f&#xff1a;\u6279\u91cf\u751f\u6210\u4e0d\u80fd\u53ea\u68c0\u67e5\u7a0b\u5e8f\u6709\u6ca1\u6709\u62a5\u9519&#xff0c;\u8fd8\u8981\u68c0\u67e5\u6587\u4ef6\u80fd\u5426\u89e3\u7801\u3001\u5c3a\u5bf8\u662f\u5426\u6b63\u786e&#xff0c;\u4ee5\u53ca\u662f\u5426\u51fa\u73b0\u7eaf\u9ed1\u7b49\u5f02\u5e38\u7ed3\u679c\u3002<\/p>\n<h2>4. \u603b\u7ed3\u4e0e\u90e8\u7f72\u5efa\u8bae<\/h2>\n<p>\u2003\u2003\u8fd9\u6b21\u6392\u67e5\u6539\u53d8\u4e86\u6211\u5bf9\u6700\u521d OOM \u7684\u5224\u65ad\u3002\u95ee\u9898\u51fa\u73b0\u5728\u4e3b\u673a\u9875\u9501\u5b9a\u5185\u5b58\u5206\u914d\u9636\u6bb5&#xff0c;\u5355\u7eaf\u964d\u4f4e\u663e\u5b58\u6863\u4f4d\u5e76\u6ca1\u6709\u7ed5\u5f00\u5b83\u3002\u5728\u5f53\u524d WSL2 \u914d\u7f6e\u4e0b&#xff0c;\u4e24\u79cd\u63a2\u6d4b\u65b9\u5f0f\u90fd\u5728\u7d2f\u8ba1\u6210\u529f\u5206\u914d 31 GiB \u540e\u5931\u8d25&#xff0c;\u800c A100 \u539f\u751f Linux \u73af\u5883\u53ef\u4ee5\u901a\u8fc7\u76f8\u5e94\u521d\u59cb\u5316\u3002\u4e0d\u8fc7&#xff0c;\u6362\u5230 A100 \u8dd1\u901a\u4e0d\u7b49\u4e8e\u5df2\u7ecf\u786e\u8ba4\u4e86 WSL2 \u7684\u5e95\u5c42\u9650\u5236\u673a\u5236&#xff0c;\u4e5f\u4e0d\u610f\u5473\u7740\u6240\u6709 16GB \u663e\u5361\u90fd\u65e0\u6cd5\u4f7f\u7528\u5b98\u65b9\u8def\u5f84\u3002\u90e8\u7f72\u65f6\u5e94\u68c0\u67e5\u81ea\u5df1\u7684\u73af\u5883&#xff0c;\u4e0d\u80fd\u76f4\u63a5\u5957\u7528\u672c\u6587\u7684 31 GiB\u3002 \u2003 \u2003\u2003\u5bf9\u4e8e\u672c\u5730\u8fd9\u5f20\u5361&#xff0c;\u66f4\u6709\u6548\u7684\u5904\u7406\u662f\u66f4\u6362\u5378\u8f7d\u8def\u5f84\u3002sequential offload \u8ba9\u6a21\u578b\u5b8c\u6210\u4e86\u751f\u6210&#xff0c;LoRA-8 \u53c8\u5c06\u672c\u6b21 2048\u00d72048 \u6d4b\u8bd5\u7f29\u77ed\u5230\u7ea6 48 \u79d2\u3002A100 \u4e0a\u7684\u6587\u751f\u56fe\u548c\u4fe1\u606f\u56fe\u52a0\u901f\u5e45\u5ea6\u66f4\u5927&#xff0c;\u4f46\u7f16\u8f91\u4efb\u52a1\u53ea\u6709 2.65 \u500d&#xff0c;\u957f\u6307\u4ee4\u7684\u7ea6\u675f\u8bc4\u5206\u4e5f\u6709\u6240\u4e0b\u964d\u3002\u901f\u5ea6\u548c\u8d28\u91cf\u90fd\u9700\u8981\u6309\u4efb\u52a1\u5206\u522b\u770b\u3002<\/p>\n<table>\n<tr>\u4f7f\u7528\u573a\u666f\u672c\u6b21\u6d4b\u8bd5\u53ef\u4f9b\u53c2\u8003\u7684\u914d\u7f6e\u4f7f\u7528\u65f6\u9700\u8981\u7559\u610f<\/tr>\n<tbody>\n<tr>\n<td>16GB &#043; WSL2&#xff0c;\u5148\u9a8c\u8bc1\u80fd\u5426\u8fd0\u884c<\/td>\n<td>sequential &#043; Base-50&#xff0c;2048\u00d72048 \u7ea6 7.3 \u5206\u949f\/\u5f20<\/td>\n<td>\u68c0\u67e5\u4e3b\u673a\u5185\u5b58\u4f59\u91cf<\/td>\n<\/tr>\n<tr>\n<td>16GB &#043; WSL2&#xff0c;\u672c\u5730\u8bd5\u56fe<\/td>\n<td>sequential &#043; LoRA-8&#xff0c;2048\u00d72048 \u7ea6 48 \u79d2\/\u5f20<\/td>\n<td>\u672c\u5730\u4ec5\u4e00\u7ec4\u914d\u5bf9\u8ba1\u65f6&#xff0c;\u6587\u5b57\u9700\u590d\u6838<\/td>\n<\/tr>\n<tr>\n<td>A100&#xff0c;\u6279\u91cf\u6587\u751f\u56fe<\/td>\n<td>full &#043; LoRA-8&#xff0c;1024\u00d71024 \u5e73\u5747\u7ea6 1.43 \u79d2\/\u5f20<\/td>\n<td>\u4e0d\u5305\u542b\u6240\u6709\u4efb\u52a1\u548c\u521d\u59cb\u5316\u5f00\u9500<\/td>\n<\/tr>\n<tr>\n<td>\u9ad8\u5206\u8fa8\u7387\u4e2d\u6587\u4fe1\u606f\u56fe<\/td>\n<td>A100 &#043; LoRA-8&#xff0c;\u672c\u4f8b 1536\u00d72720 \u7ea6 5.6 \u79d2\/\u5f20<\/td>\n<td>\u68c0\u67e5\u6587\u5b57\u3001\u5e03\u5c40\u548c\u5185\u5bb9\u5bf9\u5e94\u5173\u7cfb<\/td>\n<\/tr>\n<tr>\n<td>\u56fe\u50cf\u7f16\u8f91<\/td>\n<td>\u672c\u6b21\u4f7f\u7528 fast \u6a21\u5f0f<\/td>\n<td>full \u6a21\u5f0f\u53ef\u80fd\u56e0\u4efb\u52a1\u989d\u5916\u5f00\u9500\u800c OOM<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u2003\u2003\u5982\u679c\u4f60\u9047\u5230\u76f8\u4f3c\u95ee\u9898&#xff0c;\u53ef\u4ee5\u5148\u770b\u8c03\u7528\u6808&#xff0c;\u800c\u4e0d\u662f\u8fde\u7eed\u66f4\u6362\u751f\u6210\u53c2\u6570\u3002\u5931\u8d25\u53d1\u751f\u5728 pin_memory()&#xff0c;\u5c31\u68c0\u67e5\u4e3b\u673a\u4fa7\u5206\u914d&#xff1b;\u6743\u91cd\u80fd\u52a0\u8f7d\u3001\u63a8\u7406\u4e2d\u9014\u624d OOM&#xff0c;\u518d\u68c0\u67e5\u5206\u8fa8\u7387\u3001\u6ce8\u610f\u529b\u5b9e\u73b0\u548c\u8fd0\u884c\u65f6\u663e\u5b58\u5cf0\u503c\u3002\u5982\u679c\u4efb\u52a1\u91cc\u6709\u5927\u91cf\u5c0f\u5b57\u3001\u8868\u683c\u6216\u7cbe\u786e\u6570\u91cf\u8981\u6c42&#xff0c;\u8dd1\u901a\u4e4b\u540e\u8fd8\u5f97\u7559\u65f6\u95f4\u9a8c\u56fe\u3002\u4e00\u6b21 OCR 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