{"id":471,"date":"2025-11-25T09:21:42","date_gmt":"2025-11-25T01:21:42","guid":{"rendered":"https:\/\/high-flyer.in.suopu.cc\/?p=471"},"modified":"2025-11-25T09:21:42","modified_gmt":"2025-11-25T01:21:42","slug":"hfai-images-%e8%87%aa%e5%ae%9a%e4%b9%89%e9%95%9c%e5%83%8f%ef%bc%8c%e8%a7%a3%e5%86%b3%e7%8e%af%e5%a2%83%e9%85%8d%e7%bd%ae%e7%9a%84%e6%9c%80%e5%90%8e%e4%b8%80%e9%87%8c%e8%b7%af","status":"publish","type":"post","link":"https:\/\/high-flyer.in.suopu.cc\/en\/blog\/471\/","title":{"rendered":"hfai images | \u81ea\u5b9a\u4e49\u955c\u50cf\uff0c\u89e3\u51b3\u73af\u5883\u914d\u7f6e\u7684\u6700\u540e\u4e00\u91cc\u8def"},"content":{"rendered":"

Phantom AI has released its years-long sedimentaryDeep Learning Suite hfai<\/a>\u00a0\uff0c\u5438\u5f15\u4e86\u4f17\u591a\u540c\u884c\u7814\u7a76\u5458\u548c\u5f00\u53d1\u8005\u4eec\u54a8\u8be2\u8bd5\u7528\u3002\u6574\u4e2a\u5957\u4ef6\u7684\u529f\u80fd\u8f83\u591a\uff0c\u800c\u719f\u6089\u638c\u63e1\u4e86\u8fd9\u5957\u89c4\u5219\uff0c\u662f\u80fd\u591f\u8f7b\u677e\u5730\u8c03\u7528\u8d77\u5e73\u53f0\u7684\u7b97\u529b\u8d44\u6e90\uff0c\u4ece\u800c\u9ad8\u6548\u5b8c\u6210\u8bad\u7ec3\u4efb\u52a1\u7684\u3002\u4e3a\u6b64\uff0c\u6211\u4eec\u4e13\u95e8\u521b\u5efa\u4e86 \u201chfai \u4f7f\u7528\u5fc3\u6cd5\u201d \u7cfb\u5217\u4e13\u8f91\uff0c\u9646\u7eed\u4e3a\u5927\u5bb6\u4ecb\u7ecd hfai \u4e00\u4e9b\u529f\u80fd\u7684\u8bbe\u8ba1\u601d\u8def\u548c\u539f\u7406\uff0c\u5e2e\u52a9\u5927\u5bb6\u66f4\u5feb\u4e0a\u624b hfai\uff0c\u6e38\u5203\u6709\u4f59\u7684\u5e94\u5bf9\u6df1\u5ea6\u5b66\u4e60\u4f5c\u4e1a\u7684\u5404\u9879\u6311\u6218\u3002<\/p>\n

\u4e4b\u524d\u7684\u6587\u7ae0\u4e3a\u5927\u5bb6\u4ecb\u7ecd\u4e86\u4f7f\u7528\u00a0haienv<\/code><\/a>\u00a0\u6784\u5efa\u8fd0\u884c\u73af\u5883\u548c\u6267\u884c\u4efb\u52a1\uff0c\u7136\u800c\u5bf9\u4e8e\u4e00\u4e9b\u7279\u6b8a\u7684\u573a\u666f\uff0c\u5982\u5f3a\u5316\u5b66\u4e60\u3001\u7269\u7406\u4eff\u771f\u7b49\uff0c\u5355\u5355\u901a\u8fc7\u5b89\u88c5 Python \u4f9d\u8d56\u5df2\u4e0d\u8db3\u4ee5\u6ee1\u8db3\u9700\u6c42\u3002\u7814\u7a76\u8005\u5f80\u5f80\u4f1a\u6784\u5efa\u9879\u76ee\u7279\u6709\u955c\u50cf\u3002\u5982\u4f55\u5c06\u8fd9\u7c7b\u9700\u6c42\u5728\u8424\u706b\u96c6\u7fa4\u4e0a\u652f\u6301\u662f\u5e7b\u65b9 AI \u7814\u53d1\u8005\u4eec\u5728\u601d\u8003\u7814\u7a76\u7684\u95ee\u9898\u3002<\/p>\n

\u6700\u8fd1\uff0chfai images<\/code>\u00a0\u529f\u80fd\u9762\u4e16\uff0c\u4e3a\u7814\u7a76\u8005\u548c\u5f00\u53d1\u8005\u4eec\u63d0\u4f9b\u4e86\u4e00\u5957\u89e3\u51b3\u6b64\u7c7b\u65b9\u6cd5\u7684\u7edd\u62db\u3002\u672c\u671f\u6587\u7ae0\u5c06\u4e3a\u5927\u5bb6\u8be6\u7ec6\u4ecb\u7ecd\u3002<\/p>\n

Usage Scenarios<\/h2>\n

\u5982\u4e0a\u4e00\u671f\u6587\u7ae0\u6240\u4ecb\u7ecd<\/a>\u7684\uff0chaienv \u4e3a\u8424\u706b\u96c6\u7fa4\u7684\u7528\u6237\u63d0\u4f9b\u4e86\u81ea\u5efa Python \u8fd0\u884c\u73af\u5883\u7684\u80fd\u529b\uff0c\u5176\u652f\u6301 pip, conda \u4e24\u79cd\u65b9\u5f0f\u6ee1\u8db3\u5927\u90e8\u5206\u7528\u6237\u73af\u5883\u6784\u5efa\u7684\u9700\u6c42\u3002<\/p>\n

\u800c\u00a0hfai images<\/code>\u00a0\u89e3\u51b3\u7684\u662f\u4e00\u4e9b\u975e Python \u73af\u5883\u5b89\u88c5\u7684\u95ee\u9898<\/strong>\uff0c\u6bd4\u5982\u7269\u7406\u4eff\u771f\u91cc\u8981\u5b89\u88c5\u6a21\u62df\u5668\uff0c\u5206\u5b50\u8ba1\u7b97\u5de5\u5177\u7b49\u3002<\/p>\n

\u5e7b\u65b9 AI \u5bf9\u96c6\u7fa4\u4e2d\u7684\u955c\u50cf\u8fdb\u884c\u4e86\u6df1\u5ea6\u4f18\u5316\u548c\u5c01\u88c5\uff0c\u4ee5\u6ee1\u8db3\u8424\u706b\u96c6\u7fa4\u9ad8\u6027\u80fd\u7684\u6df1\u5ea6\u5b66\u4e60\u8bad\u7ec3\u8981\u6c42\u3002\u56e0\u6b64 hfai \u867d\u652f\u6301\u7528\u6237\u7684\u81ea\u6709\u955c\u50cf\u6784\u5efa\uff0c\u4f46\u9700\u8981\u7b26\u5408 hfai \u7684\u89c4\u8303\u548c\u6d41\u7a0b\uff0c\u5176\u8fc7\u7a0b\u9700\u8981\u5e7b\u65b9\u7ba1\u7406\u5458\u7684\u53c2\u4e0e\u548c\u652f\u6301<\/strong>\u3002<\/p>\n

\u5728\u786e\u5b9a\u4f7f\u7528\u00a0hfai images<\/code>\u00a0\u4e4b\u524d\uff0c\u8bf7\u60a8\u5ba1\u89c6\u81ea\u5df1\u7684\u73af\u5883\u5b89\u88c5\u9700\u6c42\uff0c\u786e\u5b9a\u53ea\u6709\u81ea\u6709\u955c\u50cf\u8fd9\u4e00\u6761\u8def\u6bd4\u8f83\u65b9\u4fbf\u540e\uff0c\u53ef\u4ee5\u548c\u7ba1\u7406\u5458\u8054\u7cfb<\/a>\u3002<\/p>\n

\u4f7f\u7528\u6d41\u7a0b<\/h2>\n

hfai images<\/code>\u00a0\u7684\u4f7f\u7528\u6d41\u7a0b\u5305\u542b\u5982\u4e0b\u51e0\u6b65\uff1a<\/p>\n

    \n
  1. \u83b7\u53d6\u96c6\u7fa4\u4e2d\u7684 base \u955c\u50cf\u7684 tar \u5305\u3002\u6211\u4eec\u63d0\u4f9b\u4e86\u00a0cuda_111<\/code>\u00a0\u548c\u00a0cuda_113<\/code>\u00a0\u4e24\u4e2a\u7248\u672c\uff0c\u57fa\u4e8e\u00a0Ubuntu 20.04<\/code>\uff1b<\/li>\n
  2. \u5728\u672c\u5730\u52a0\u8f7d\u4e0a\u8ff0 tar \u5305\uff0c\u6bd4\u5982\u00a0registry.high-flyer.cn\/platform\/hf_training:ubuntu2004-cu113-20221019<\/code>\uff1b<\/li>\n
  3. \u57fa\u4e8e\u4e0a\u8ff0 base \u955c\u50cf\u6784\u5efa\u81ea\u5df1\u7684\u955c\u50cf\uff08\u6bd4\u5982\u00a0python:3.8-alpine<\/code>\uff09\uff1b<\/li>\n
  4. docker save<\/code>\u00a0\u81ea\u5df1\u7684\u955c\u50cf\uff0c\u4fdd\u5b58\u6210 tar \u5305\uff08\u6bd4\u5982\u00a0python-alpine.tar<\/code>\uff09\uff0c\u901a\u8fc7\u00a0hfai workspace<\/code>\u00a0\u4e0a\u4f20\u5230\u8424\u706b\u96c6\u7fa4\uff1b<\/li>\n
  5. \u6253\u5f00 Studio\u00a0\u8fdb\u5165 workspace \u76ee\u5f55<\/a>\uff0c\u4f7f\u7528\u00a0hfai images load<\/code>\u00a0\u547d\u4ee4\uff08\u6bd4\u5982\u00a0hfai images load python-alpine.tar<\/code>\uff09\uff1b<\/li>\n
  6. \u7b49\u5f85\u5b8c\u6210\uff0c\u53ef\u4ee5\u901a\u8fc7\u00a0hfai images list<\/code>\u00a0\u547d\u4ee4\u67e5\u770b\u3002\u8fd9\u91cc\u955c\u50cf\u52a0\u8f7d\u5b8c\u6210\u540e\u8fd4\u56de\u5982\u4e0b\u7ed3\u679c\uff1a\n

    \"hfai<\/a><\/span><\/li>\n

  7. \u7b49\u72b6\u6001\u53d8\u6210\u00a0loaded<\/code>\u00a0\u4e4b\u540e\uff0c\u60a8\u624d\u53ef\u4ee5\u901a\u8fc7\u00a0hfai python test.py -- -n 1 --image registry.high-flyer.cn\/hfai\/python:3.8-alpine<\/code>\u00a0\u6765\u4f7f\u7528\u60a8\u6240\u6784\u5efa\u7684\u955c\u50cf\u3002<\/li>\n<\/ol>","protected":false},"excerpt":{"rendered":"

    \u5e7b\u65b9 AI \u53d1\u5e03\u4e86\u5176\u6c89\u6dc0\u591a\u5e74\u7684\u6df1\u5ea6\u5b66\u4e60\u5957\u4ef6 hfai\u00a0\uff0c\u5438\u5f15\u4e86\u4f17\u591a\u540c\u884c\u7814\u7a76\u5458\u548c\u5f00\u53d1\u8005\u4eec\u54a8\u8be2\u8bd5\u7528\u3002\u6574\u4e2a\u5957\u4ef6\u7684\u529f\u80fd […]<\/p>","protected":false},"author":1,"featured_media":472,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[7],"tags":[],"class_list":["post-471","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-hfai-mantra"],"acf":[],"_links":{"self":[{"href":"https:\/\/high-flyer.in.suopu.cc\/en\/wp-json\/wp\/v2\/posts\/471","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/high-flyer.in.suopu.cc\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/high-flyer.in.suopu.cc\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/high-flyer.in.suopu.cc\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/high-flyer.in.suopu.cc\/en\/wp-json\/wp\/v2\/comments?post=471"}],"version-history":[{"count":1,"href":"https:\/\/high-flyer.in.suopu.cc\/en\/wp-json\/wp\/v2\/posts\/471\/revisions"}],"predecessor-version":[{"id":473,"href":"https:\/\/high-flyer.in.suopu.cc\/en\/wp-json\/wp\/v2\/posts\/471\/revisions\/473"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/high-flyer.in.suopu.cc\/en\/wp-json\/wp\/v2\/media\/472"}],"wp:attachment":[{"href":"https:\/\/high-flyer.in.suopu.cc\/en\/wp-json\/wp\/v2\/media?parent=471"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/high-flyer.in.suopu.cc\/en\/wp-json\/wp\/v2\/categories?post=471"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/high-flyer.in.suopu.cc\/en\/wp-json\/wp\/v2\/tags?post=471"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}