{"id":28905,"date":"2025-03-18T00:16:16","date_gmt":"2025-03-17T16:16:16","guid":{"rendered":"https:\/\/www.aisharenet.com\/?p=28905"},"modified":"2025-03-18T00:16:16","modified_gmt":"2025-03-17T16:16:16","slug":"mm-eureka","status":"publish","type":"post","link":"https:\/\/www.kdjingpai.com\/de\/mm-eureka\/","title":{"rendered":"MM-EUREKA\uff1a\u63a2\u7d22\u89c6\u89c9\u63a8\u7406\u7684\u591a\u6a21\u6001\u5f3a\u5316\u5b66\u4e60\u5de5\u5177"},"content":{"rendered":"<p>MM-EUREKA \u662f\u4e00\u4e2a\u7531\u4e0a\u6d77\u4eba\u5de5\u667a\u80fd\u5b9e\u9a8c\u5ba4\u3001\u4e0a\u6d77\u4ea4\u901a\u5927\u5b66\u7b49\u591a\u65b9\u5408\u4f5c\u5f00\u53d1\u7684\u5f00\u6e90\u9879\u76ee\u3002\u5b83\u901a\u8fc7\u57fa\u4e8e\u89c4\u5219\u7684\u5f3a\u5316\u5b66\u4e60\u6280\u672f\uff0c\u628a\u6587\u672c\u63a8\u7406\u80fd\u529b\u6269\u5c55\u5230\u591a\u6a21\u6001\u573a\u666f\uff0c\u5e2e\u52a9\u6a21\u578b\u5904\u7406\u56fe\u50cf\u548c\u6587\u5b57\u4fe1\u606f\u3002\u8fd9\u4e2a\u5de5\u5177\u7684\u6838\u5fc3\u76ee\u6807\u662f\u63d0\u5347\u6a21\u578b\u5728\u89c6\u89c9\u548c\u6570\u5b66\u63a8\u7406\u4efb\u52a1\u4e0a\u7684\u8868\u73b0\u3002\u5b83\u63a8\u51fa\u4e86\u4e24\u4e2a\u4e3b\u8981\u6a21\u578b\uff1aMM-Eureka-8B \u548c MM-Eureka-Zero-38B\u3002\u5b83\u4eec\u80fd\u5728\u5c11\u91cf\u6570\u636e\u4e0b\u5b9e\u73b0\u9ad8\u6548\u8bad\u7ec3\uff0c\u6bd4\u5982\u4ec5\u7528 54K \u56fe\u6587\u6570\u636e\u5c31\u80fd\u8d85\u8d8a\u5176\u4ed6\u9700\u8981\u767e\u4e07\u7ea7\u6570\u636e\u7684\u6a21\u578b\u3002\u9879\u76ee\u5b8c\u5168\u5f00\u6e90\uff0c\u4ee3\u7801\u3001\u6a21\u578b\u548c\u6570\u636e\u90fd\u53ef\u4ee5\u5728 GitHub \u4e0a\u514d\u8d39\u83b7\u53d6\uff0c\u9002\u5408\u7814\u7a76\u4eba\u5458\u548c\u5f00\u53d1\u8005\u63a2\u7d22\u591a\u6a21\u6001\u63a8\u7406\u6280\u672f\u3002<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"\" title=\"MM-EUREKA\uff1a\u63a2\u7d22\u89c6\u89c9\u63a8\u7406\u7684\u591a\u6a21\u6001\u5f3a\u5316\u5b66\u4e60\u5de5\u5177-1\" src=\"https:\/\/www.kdjingpai.com\/wp-content\/uploads\/2025\/03\/b62f40c41258f70.jpg\" alt=\"MM-EUREKA\uff1a\u63a2\u7d22\u89c6\u89c9\u63a8\u7406\u7684\u591a\u6a21\u6001\u5f3a\u5316\u5b66\u4e60\u5de5\u5177-1\" width=\"799\" height=\"648\" \/><\/p>\n<p>&nbsp;<\/p>\n<h2>\u529f\u80fd\u5217\u8868<\/h2>\n<ul>\n<li>\u652f\u6301\u591a\u6a21\u6001\u63a8\u7406\uff1a\u80fd\u540c\u65f6\u5904\u7406\u56fe\u50cf\u548c\u6587\u672c\uff0c\u63d0\u5347\u6a21\u578b\u7406\u89e3\u590d\u6742\u95ee\u9898\u7684\u80fd\u529b\u3002<\/li>\n<li>\u57fa\u4e8e\u89c4\u5219\u7684\u5f3a\u5316\u5b66\u4e60\uff1a\u901a\u8fc7\u7b80\u5355\u89c4\u5219\u8bad\u7ec3\u6a21\u578b\uff0c\u51cf\u5c11\u5bf9\u5927\u89c4\u6a21\u6570\u636e\u7684\u4f9d\u8d56\u3002<\/li>\n<li>\u89c6\u89c9\u987f\u609f\u80fd\u529b\uff1a\u6a21\u578b\u80fd\u5728\u63a8\u7406\u4e2d\u91cd\u65b0\u5ba1\u89c6\u56fe\u50cf\u7ebf\u7d22\uff0c\u6a21\u62df\u4eba\u7c7b\u53cd\u601d\u8fc7\u7a0b\u3002<\/li>\n<li>\u5f00\u6e90\u5b8c\u6574\u7ba1\u9053\uff1a\u63d0\u4f9b\u4ee3\u7801\u3001\u6570\u636e\u96c6\u548c\u8bad\u7ec3\u6d41\u7a0b\uff0c\u65b9\u4fbf\u7528\u6237\u590d\u73b0\u548c\u6539\u8fdb\u3002<\/li>\n<li>\u9ad8\u6570\u636e\u6548\u7387\uff1a\u5728\u5c11\u91cf\u6570\u636e\uff08\u5982 8K \u6216 54K \u56fe\u6587\u5bf9\uff09\u4e0b\uff0c\u6027\u80fd\u5ab2\u7f8e\u767e\u4e07\u7ea7\u6570\u636e\u8bad\u7ec3\u7684\u6a21\u578b\u3002<\/li>\n<li>\u6570\u5b66\u63a8\u7406\u652f\u6301\uff1a\u7279\u522b\u4f18\u5316\u4e86\u6570\u5b66\u95ee\u9898\u89e3\u51b3\u80fd\u529b\uff0c\u9002\u7528\u4e8e\u6559\u80b2\u548c\u5b66\u672f\u573a\u666f\u3002<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h2>\u4f7f\u7528\u5e2e\u52a9<\/h2>\n<p>MM-EUREKA \u662f\u4e00\u4e2a\u57fa\u4e8e GitHub \u7684\u5f00\u6e90\u9879\u76ee\uff0c\u4e3b\u8981\u9762\u5411\u6709\u4e00\u5b9a\u7f16\u7a0b\u57fa\u7840\u7684\u7528\u6237\uff0c\u5c24\u5176\u662f\u7814\u7a76\u4eba\u5458\u548c\u5f00\u53d1\u8005\u3002\u4e0b\u9762\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u5b89\u88c5\u548c\u4f7f\u7528\u8fd9\u4e2a\u5de5\u5177\uff0c\u5305\u62ec\u4e3b\u8981\u529f\u80fd\u7684\u5b9e\u9645\u64cd\u4f5c\u6d41\u7a0b\u3002<\/p>\n<h3>\u5b89\u88c5\u6d41\u7a0b<\/h3>\n<ol>\n<li><strong>\u51c6\u5907\u73af\u5883<\/strong>\n<ul>\n<li>\u786e\u4fdd\u4f60\u7684\u7535\u8111\u5df2\u5b89\u88c5 Python 3.8 \u6216\u66f4\u9ad8\u7248\u672c\u3002\u53ef\u4ee5\u7528\u547d\u4ee4\u00a0<code>python --version<\/code>\u00a0\u68c0\u67e5\u3002<\/li>\n<li>\u9700\u8981\u5b89\u88c5 Git \u6765\u514b\u9686\u4ee3\u7801\u3002\u5982\u679c\u6ca1\u6709 Git\uff0c\u53ef\u4ee5\u5728\u5b98\u7f51\u4e0b\u8f7d\u5e76\u5b89\u88c5\u3002<\/li>\n<li>\u63a8\u8350\u4f7f\u7528 Linux \u7cfb\u7edf\uff08\u5982 Ubuntu 20.04 \u6216 22.04\uff09\uff0cWindows \u7528\u6237\u53ef\u80fd\u9700\u8981\u989d\u5916\u914d\u7f6e\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u514b\u9686\u9879\u76ee\u4ee3\u7801<\/strong>\n<ul>\n<li>\u6253\u5f00\u7ec8\u7aef\uff0c\u8f93\u5165\u4ee5\u4e0b\u547d\u4ee4\u4e0b\u8f7d MM-EUREKA \u6e90\u7801\uff1a\n<pre><code>git clone https:\/\/github.com\/ModalMinds\/MM-EUREKA.git\r\n<\/code><\/pre>\n<\/li>\n<li>\u4e0b\u8f7d\u5b8c\u6210\u540e\uff0c\u8fdb\u5165\u9879\u76ee\u6587\u4ef6\u5939\uff1a\n<pre><code>cd MM-EUREKA\r\n<\/code><\/pre>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u5b89\u88c5\u4f9d\u8d56<\/strong>\n<ul>\n<li>\u8fd0\u884c\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\u57fa\u672c\u4f9d\u8d56\uff1a\n<pre><code>pip install -e .\r\n<\/code><\/pre>\n<\/li>\n<li>\u5982\u679c\u9700\u8981\u4f7f\u7528 <a href=\"https:\/\/www.kdjingpai.com\/de\/vllm\/\">vLLM<\/a> \u52a0\u901f\u63a8\u7406\uff0c\u8fd8\u9700\u5b89\u88c5\u989d\u5916\u5305\uff1a\n<pre><code>pip install -e .[vllm]\r\n<\/code><\/pre>\n<\/li>\n<li>\u5b89\u88c5 Flash-Attention\uff08\u7248\u672c 2.3.6\uff09\u4ee5\u63d0\u5347\u6027\u80fd\uff1a\n<pre><code>pip install flash-attn==2.3.6 --no-build-isolation\r\n<\/code><\/pre>\n<p>\u5982\u679c\u9047\u5230\u95ee\u9898\uff0c\u53ef\u4ee5\u5c1d\u8bd5\u4ece\u6e90\u7801\u5b89\u88c5\uff1a<\/p>\n<pre><code>git clone https:\/\/github.com\/Dao-AILab\/flash-attention.git\r\ncd flash-attention\r\ngit checkout v2.3.6\r\npython setup.py install\r\n<\/code><\/pre>\n<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u4e0b\u8f7d\u6570\u636e\u96c6<\/strong>\n<ul>\n<li>\u9879\u76ee\u63d0\u4f9b\u8bad\u7ec3\u6570\u636e MM-Eureka-Dataset\uff0c\u53ef\u4ee5\u4ece GitHub Releases \u4e0b\u8f7d\u3002<\/li>\n<li>\u4e0b\u8f7d\u540e\uff0c\u89e3\u538b\u6587\u4ef6\uff0c\u5e76\u6839\u636e\u9700\u8981\u4fee\u6539\u6570\u636e\u4e2d\u7684\u00a0<code>image_urls<\/code>\u00a0\u5b57\u6bb5\uff0c\u6307\u5411\u672c\u5730\u56fe\u7247\u8def\u5f84\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u9a8c\u8bc1\u5b89\u88c5<\/strong>\n<ul>\n<li>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u8fd0\u884c\u00a0<code>python -c \"import mm_eureka\"<\/code>\u00a0\u68c0\u67e5\u662f\u5426\u62a5\u9519\u3002\u5982\u679c\u6ca1\u6709\u9519\u8bef\uff0c\u8bf4\u660e\u5b89\u88c5\u6210\u529f\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<h3>\u4f7f\u7528\u4e3b\u8981\u529f\u80fd<\/h3>\n<h4>\u529f\u80fd 1\uff1a\u8fd0\u884c\u591a\u6a21\u6001\u63a8\u7406\u6a21\u578b<\/h4>\n<ul>\n<li><strong>\u51c6\u5907\u6570\u636e<\/strong>\n<ul>\n<li>\u6570\u636e\u9700\u6309 JSONL \u683c\u5f0f\u7ec4\u7ec7\uff0c\u6bcf\u884c\u662f\u4e00\u4e2a\u5b57\u5178\uff0c\u5305\u542b\u00a0<code>id<\/code>\u3001<code>conversations<\/code>\u3001<code>answer<\/code>\u00a0\u548c\u00a0<code>image_urls<\/code>\u00a0\u5b57\u6bb5\u3002\u4f8b\u5982\uff1a\n<pre><code>{\"id\": \"0\", \"conversations\": [{\"role\": \"user\", \"content\": \"\u8fd9\u5f20\u56fe\u91cc\u7684\u6570\u5b66\u9898\u7b54\u6848\u662f\u4ec0\u4e48\uff1f\"}], \"answer\": \"42\", \"image_urls\": [\"file:\/\/\/path\/to\/image.jpg\"]}\r\n<\/code><\/pre>\n<\/li>\n<li>\u628a\u6570\u636e\u4fdd\u5b58\u4e3a\u00a0<code>dataset.jsonl<\/code>\uff0c\u653e\u5728\u9879\u76ee\u76ee\u5f55\u4e0b\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u8fd0\u884c\u63a8\u7406<\/strong>\n<ul>\n<li>\u5728\u7ec8\u7aef\u8f93\u5165\u4ee5\u4e0b\u547d\u4ee4\u52a0\u8f7d\u6a21\u578b\u5e76\u63a8\u7406\uff1a\n<pre><code>python scripts\/inference.py --model MM-Eureka-8B --data dataset.jsonl\r\n<\/code><\/pre>\n<\/li>\n<li>\u8f93\u51fa\u4f1a\u663e\u793a\u6a21\u578b\u5bf9\u6bcf\u4e2a\u95ee\u9898\u7684\u63a8\u7406\u8fc7\u7a0b\u548c\u7b54\u6848\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h4>\u529f\u80fd 2\uff1a\u8bad\u7ec3\u81ea\u5b9a\u4e49\u6a21\u578b<\/h4>\n<ul>\n<li><strong>\u914d\u7f6e\u8bad\u7ec3\u53c2\u6570<\/strong>\n<ul>\n<li>\u6253\u5f00\u00a0<code>config.yaml<\/code>\u00a0\u6587\u4ef6\uff0c\u8bbe\u7f6e\u6a21\u578b\u53c2\u6570\uff08\u5982\u5b66\u4e60\u7387\u3001\u6279\u6b21\u5927\u5c0f\uff09\u548c\u6570\u636e\u8def\u5f84\u3002<\/li>\n<li>\u786e\u4fdd\u00a0<code>data_path<\/code>\u00a0\u6307\u5411\u4f60\u7684\u00a0<code>dataset.jsonl<\/code>\u00a0\u6587\u4ef6\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u542f\u52a8\u8bad\u7ec3<\/strong>\n<ul>\n<li>\u8fd0\u884c\u4ee5\u4e0b\u547d\u4ee4\u5f00\u59cb\u8bad\u7ec3\uff1a\n<pre><code>python scripts\/train.py --config config.yaml\r\n<\/code><\/pre>\n<\/li>\n<li>\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\uff0c\u6a21\u578b\u4f1a\u4fdd\u5b58\u68c0\u67e5\u70b9\u5230\u00a0<code>checkpoints\/<\/code>\u00a0\u6587\u4ef6\u5939\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h4>\u529f\u80fd 3\uff1a\u6d4b\u8bd5\u89c6\u89c9\u987f\u609f\u80fd\u529b<\/h4>\n<ul>\n<li><strong>\u51c6\u5907\u6d4b\u8bd5\u6570\u636e<\/strong>\n<ul>\n<li>\u4f7f\u7528\u5305\u542b\u56fe\u50cf\u7684\u590d\u6742\u6570\u5b66\u95ee\u9898\u6570\u636e\uff0c\u6bd4\u5982\u4ece K12 \u6570\u636e\u96c6\u6311\u9009\u51e0\u9053\u9898\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u8fd0\u884c\u6d4b\u8bd5<\/strong>\n<ul>\n<li>\u8f93\u5165\u547d\u4ee4\uff1a\n<pre><code>python scripts\/test_reflection.py --model MM-Eureka-Zero-38B --data test.jsonl\r\n<\/code><\/pre>\n<\/li>\n<li>\u6a21\u578b\u4f1a\u5c55\u793a\u63a8\u7406\u8fc7\u7a0b\uff0c\u5305\u62ec\u5982\u4f55\u91cd\u65b0\u68c0\u67e5\u56fe\u50cf\u7ebf\u7d22\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3>\u64cd\u4f5c\u6d41\u7a0b\u793a\u4f8b\uff1a\u89e3\u51b3\u6570\u5b66\u95ee\u9898<\/h3>\n<ol>\n<li><strong>\u4e0a\u4f20\u6570\u636e<\/strong>\n<ul>\n<li>\u51c6\u5907\u4e00\u5f20\u56fe\u7247\uff08\u6bd4\u5982\u51e0\u4f55\u9898\uff09\u548c\u5bf9\u5e94\u7684\u95ee\u9898\u63cf\u8ff0\uff0c\u4fdd\u5b58\u4e3a JSONL \u683c\u5f0f\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u8fd0\u884c\u6a21\u578b<\/strong>\n<ul>\n<li>\u7528\u00a0<code>inference.py<\/code>\u00a0\u811a\u672c\u52a0\u8f7d MM-Eureka-8B\uff0c\u8f93\u5165\u6570\u636e\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u67e5\u770b\u7ed3\u679c<\/strong>\n<ul>\n<li>\u6a21\u578b\u4f1a\u8f93\u51fa\u63a8\u7406\u6b65\u9aa4\uff08<code>&lt;think&gt;<\/code>\u00a0\u6807\u7b7e\uff09\u548c\u6700\u7ec8\u7b54\u6848\uff08<code>&lt;answer&gt;<\/code>\u00a0\u6807\u7b7e\uff09\uff0c\u6bd4\u5982\uff1a\n<pre><code>&lt;think&gt;\u5148\u770b\u56fe\uff0c\u5706\u7684\u534a\u5f84\u662f 5\uff0c\u9762\u79ef\u516c\u5f0f\u662f \u03c0r\u00b2\uff0c\u6240\u4ee5\u662f 25\u03c0\u3002&lt;\/think&gt;\r\n&lt;answer&gt;25\u03c0&lt;\/answer&gt;\r\n<\/code><\/pre>\n<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<h3>\u6ce8\u610f\u4e8b\u9879<\/h3>\n<ul>\n<li>\u5982\u679c\u9047\u5230 GPU \u5185\u5b58\u4e0d\u8db3\uff0c\u8c03\u6574\u6279\u6b21\u5927\u5c0f\u6216\u4f7f\u7528 MM-Eureka-8B\uff08\u8f83\u5c0f\u6a21\u578b\uff09\u3002<\/li>\n<li>\u6570\u636e\u4e2d\u7684\u56fe\u7247\u8def\u5f84\u5fc5\u987b\u6709\u6548\uff0c\u5426\u5219\u6a21\u578b\u65e0\u6cd5\u5904\u7406\u56fe\u50cf\u3002<\/li>\n<\/ul>\n<p>\u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u4f60\u53ef\u4ee5\u8f7b\u677e\u4e0a\u624b MM-EUREKA\uff0c\u4f53\u9a8c\u5b83\u7684\u591a\u6a21\u6001\u63a8\u7406\u80fd\u529b\u3002<\/p>\n<p>&nbsp;<\/p>\n<h2>\u5e94\u7528\u573a\u666f<\/h2>\n<ol>\n<li><strong>\u6559\u80b2\u8f85\u52a9<\/strong><br \/>\nMM-EUREKA \u80fd\u5206\u6790\u6570\u5b66\u9898\u76ee\u56fe\u7247\u5e76\u7ed9\u51fa\u8be6\u7ec6\u89e3\u9898\u6b65\u9aa4\uff0c\u9002\u5408\u5b66\u751f\u7ec3\u4e60\u6216\u8001\u5e08\u5907\u8bfe\u3002<\/li>\n<li><strong>\u79d1\u7814\u63a2\u7d22<\/strong><br \/>\n\u7814\u7a76\u4eba\u5458\u53ef\u4ee5\u7528\u5b83\u6d4b\u8bd5\u5f3a\u5316\u5b66\u4e60\u5728\u591a\u6a21\u6001\u4efb\u52a1\u4e2d\u7684\u6548\u679c\uff0c\u6539\u8fdb\u7b97\u6cd5\u6216\u5f00\u53d1\u65b0\u6a21\u578b\u3002<\/li>\n<li><strong>AR\/VR \u5f00\u53d1<\/strong><br \/>\n\u5f00\u53d1\u8005\u53ef\u4ee5\u5229\u7528\u5b83\u7684\u89c6\u89c9\u63a8\u7406\u80fd\u529b\uff0c\u6253\u9020\u66f4\u667a\u80fd\u7684\u4ea4\u4e92\u5f0f\u5e94\u7528\uff0c\u6bd4\u5982\u5b9e\u65f6\u89e3\u9898\u52a9\u624b\u3002<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n<h2>QA<\/h2>\n<ol>\n<li><strong>MM-EUREKA \u652f\u6301\u54ea\u4e9b\u8bed\u8a00\uff1f<\/strong><br \/>\n\u76ee\u524d\u4e3b\u8981\u652f\u6301\u82f1\u8bed\u548c\u4e2d\u6587\u7684\u56fe\u6587\u6570\u636e\uff0c\u6a21\u578b\u5bf9\u8fd9\u4e24\u79cd\u8bed\u8a00\u7684\u63a8\u7406\u6548\u679c\u6700\u597d\u3002<\/li>\n<li><strong>\u9700\u8981\u591a\u5f3a\u7684\u7535\u8111\u914d\u7f6e\uff1f<\/strong><br \/>\n\u5efa\u8bae\u81f3\u5c11 16GB \u5185\u5b58\u548c\u4e00\u5757\u4e2d\u7aef GPU\uff08\u5982 NVIDIA GTX 1660\uff09\u3002\u8bad\u7ec3\u5927\u6a21\u578b\u53ef\u80fd\u9700\u8981\u66f4\u5f3a\u7684\u786c\u4ef6\u3002<\/li>\n<li><strong>\u5982\u4f55\u8d21\u732e\u4ee3\u7801\uff1f<\/strong><br \/>\n\u5728 GitHub \u4e0a\u63d0\u4ea4 Pull Request\uff0c\u53c2\u8003\u00a0<code>CONTRIBUTING.md<\/code>\u00a0\u6587\u4ef6\u91cc\u7684\u6307\u5f15\u3002<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>MM-EUREKA 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