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  146. <img src="https://api.limour.top/randomImg?d=2024-03-20 11:52:10" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload alt="【记录】Linux 设置个人热点">
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  149. <article class="col-12 col-md-8 mx-auto index-info">
  150. <h2 class="index-header">
  151. <a href="/Linux-Setting-AP" target="_self">
  152. 【记录】Linux 设置个人热点
  153. </a>
  154. </h2>
  155. <a class="index-excerpt " href="/Linux-Setting-AP" target="_self">
  156. <div>
  157. 实在受不了虚拟机的性能损失了,再加上 Win11 上跑虚拟机对 SSD 的损耗过大,因此还是将系统换成了 ubuntu,只要注意选无网络安装,不要去更新,基本还是很好换系统的。另外清华源不错! 换系统后,需要重新折腾一下 AP 设置,因此记录一下折腾过程。 无线网卡是垃圾的 mediatek mt7921e 更新内核 因为网卡垃圾,不得不更新到最新的内核才支持 AP 设置 1234567proxy
  158. </div>
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  160. <div class="index-btm post-metas">
  161. <div class="post-meta mr-3">
  162. <i class="iconfont icon-date"></i>
  163. <time datetime="2024-03-20 19:52" pubdate>
  164. 2024-03-20
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  168. <i class="iconfont icon-tags"></i>
  169. <a href="/tags/ubuntu/">#ubuntu</a>
  170. </div>
  171. </div>
  172. </article>
  173. </div>
  174. <div class="row mx-auto index-card">
  175. <div class="col-12 col-md-4 m-auto index-img">
  176. <a href="/Sample-size-calculation-for-survival-analysis-in-clinical-research" target="_self">
  177. <img src="https://api.limour.top/randomImg?d=2024-03-12 16:46:35" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload alt="【探索】暴力计算临床研究的样本量">
  178. </a>
  179. </div>
  180. <article class="col-12 col-md-8 mx-auto index-info">
  181. <h2 class="index-header">
  182. <a href="/Sample-size-calculation-for-survival-analysis-in-clinical-research" target="_self">
  183. 【探索】暴力计算临床研究的样本量
  184. </a>
  185. </h2>
  186. <a class="index-excerpt " href="/Sample-size-calculation-for-survival-analysis-in-clinical-research" target="_self">
  187. <div>
  188. 这篇博客介绍了如何计算临床研究中两组生存分析的样本量。首先,作者提供了R代码,包括Logrank对数秩检验的函数以及模拟计算样本量的函数。其次,作者详细解释了模拟计算的步骤,包括生成生存时间数据、招募时间、失访时间等,并通过模拟来估计研究的功效。最后,作者展示了如何使用模拟计算函数来确定样本量,以达到预先设定的功效水平。通过模拟检验,作者展示了样本量计算的有效性,并给出了两个示例,以验证样本量计算
  189. </div>
  190. </a>
  191. <div class="index-btm post-metas">
  192. <div class="post-meta mr-3">
  193. <i class="iconfont icon-date"></i>
  194. <time datetime="2024-03-13 00:46" pubdate>
  195. 2024-03-13
  196. </time>
  197. </div>
  198. <div class="post-meta">
  199. <i class="iconfont icon-tags"></i>
  200. <a href="/tags/r/">#R</a>
  201. <a href="/tags/bootstrap/">#Bootstrap</a>
  202. </div>
  203. </div>
  204. </article>
  205. </div>
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  207. <div class="col-12 col-md-4 m-auto index-img">
  208. <a href="/Enjoy-unlimited-length-LLM-role-playing-with-6GB-of-VRAM" target="_self">
  209. <img src="https://api.limour.top/randomImg?d=2024-02-10 01:02:10" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload alt="【探索】6G显存畅玩无限长度的LLM角色扮演">
  210. </a>
  211. </div>
  212. <article class="col-12 col-md-8 mx-auto index-info">
  213. <h2 class="index-header">
  214. <a href="/Enjoy-unlimited-length-LLM-role-playing-with-6GB-of-VRAM" target="_self">
  215. 【探索】6G显存畅玩无限长度的LLM角色扮演
  216. </a>
  217. </h2>
  218. <a class="index-excerpt " href="/Enjoy-unlimited-length-LLM-role-playing-with-6GB-of-VRAM" target="_self">
  219. <div>
  220. 角色扮演的体验是否舒适主要受角色卡、大模型和生成时间三个因素的影响。 优秀的角色卡往往附带大量的设定,这会极大的拖慢第一次生成的时间,并且随着对话的进行,上下文长度很容易超过kv_cache的上限,这些很破坏沉浸式的体验。 此外,大模型在进行角色扮演时,除了进行必要的对话生成外,还需要生成旁白增加想象空间。 对博主这些相比填空更喜欢选项的玩家,给出提问建议也是非常必要的:在建议的基础上修改比自己从
  221. </div>
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  224. <div class="post-meta mr-3">
  225. <i class="iconfont icon-date"></i>
  226. <time datetime="2024-02-10 09:02" pubdate>
  227. 2024-02-10
  228. </time>
  229. </div>
  230. <div class="post-meta">
  231. <i class="iconfont icon-tags"></i>
  232. <a href="/tags/%E6%8E%A2%E7%B4%A2/">#探索</a>
  233. <a href="/tags/llama/">#llama</a>
  234. </div>
  235. </div>
  236. </article>
  237. </div>
  238. <div class="row mx-auto index-card">
  239. <div class="col-12 col-md-4 m-auto index-img">
  240. <a href="/Convert-BlueLM-7B-Chat-to-the-standard-GGUF-model" target="_self">
  241. <img src="https://api.limour.top/randomImg?d=2024-02-03 22:38:07" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload alt="【探索】将BlueLM-7B-Chat转换为标准的GGUF模型">
  242. </a>
  243. </div>
  244. <article class="col-12 col-md-8 mx-auto index-info">
  245. <h2 class="index-header">
  246. <a href="/Convert-BlueLM-7B-Chat-to-the-standard-GGUF-model" target="_self">
  247. 【探索】将BlueLM-7B-Chat转换为标准的GGUF模型
  248. </a>
  249. </h2>
  250. <a class="index-excerpt " href="/Convert-BlueLM-7B-Chat-to-the-standard-GGUF-model" target="_self">
  251. <div>
  252. 准备模型 运行环境 123456789# conda create -n llamaConvert python=3.10 git -c conda-forge# conda activate llamaConvert# cd D:\llama# git clone --depth=1 https://github.com/ggerganov/llama.cpp.git# cd llama.c
  253. </div>
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  256. <div class="post-meta mr-3">
  257. <i class="iconfont icon-date"></i>
  258. <time datetime="2024-02-04 06:38" pubdate>
  259. 2024-02-04
  260. </time>
  261. </div>
  262. <div class="post-meta">
  263. <i class="iconfont icon-tags"></i>
  264. <a href="/tags/%E6%8E%A2%E7%B4%A2/">#探索</a>
  265. <a href="/tags/llama/">#llama</a>
  266. </div>
  267. </div>
  268. </article>
  269. </div>
  270. <div class="row mx-auto index-card">
  271. <div class="col-12 col-md-4 m-auto index-img">
  272. <a href="/training-gpt-from-scratch" target="_self">
  273. <img src="https://api.limour.top/randomImg?d=2024-01-18 14:19:11" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload alt="【探索】从零开始训练 GPT">
  274. </a>
  275. </div>
  276. <article class="col-12 col-md-8 mx-auto index-info">
  277. <h2 class="index-header">
  278. <a href="/training-gpt-from-scratch" target="_self">
  279. 【探索】从零开始训练 GPT
  280. </a>
  281. </h2>
  282. <a class="index-excerpt " href="/training-gpt-from-scratch" target="_self">
  283. <div>
  284. 探索整个过程,从在一台搭载1660Ti显卡的笔记本电脑上构建 Tokenizer,定义带有 RoPE 的 Transformer,一直到训练、保存模型和可视化训练过程。沉浸在从零开始训练 GPT 的旅程中,深入了解每一个步骤。跳入深度学习的世界,释放在你的便携1660Ti笔记本上的强大潜能。
  285. </div>
  286. </a>
  287. <div class="index-btm post-metas">
  288. <div class="post-meta mr-3">
  289. <i class="iconfont icon-date"></i>
  290. <time datetime="2024-01-18 22:19" pubdate>
  291. 2024-01-18
  292. </time>
  293. </div>
  294. <div class="post-meta">
  295. <i class="iconfont icon-tags"></i>
  296. <a href="/tags/%E6%8E%A2%E7%B4%A2/">#探索</a>
  297. <a href="/tags/llama/">#llama</a>
  298. </div>
  299. </div>
  300. </article>
  301. </div>
  302. <div class="row mx-auto index-card">
  303. <div class="col-12 col-md-4 m-auto index-img">
  304. <a href="/Azure-AI-prevents-reverse-wool-shearing" target="_self">
  305. <img src="https://api.limour.top/randomImg?d=2024-01-09 05:55:40" srcset="https://jscdn.limour.top/gh/Limour-dev/Sakurairo_Vision/load_svg/inload.svg" lazyload alt="【避坑】Azure AI 避免反向薅羊毛">
  306. </a>
  307. </div>
  308. <article class="col-12 col-md-8 mx-auto index-info">
  309. <h2 class="index-header">
  310. <a href="/Azure-AI-prevents-reverse-wool-shearing" target="_self">
  311. 【避坑】Azure AI 避免反向薅羊毛
  312. </a>
  313. </h2>
  314. <a class="index-excerpt " href="/Azure-AI-prevents-reverse-wool-shearing" target="_self">
  315. <div>
  316. 起因 今天收到 Azure 的付费邮件,一看账单,好家伙,24.54$ ,比上个月暴涨 622%,给我 CPU 干烧了。 赶紧去成本分析里按资源分类看上个月的扣费详情,然后就看到两个 10.33$ 的 Container Registry,分别位于我在 Azure AI Studio 里的两个不同项目所在区域。 一顿折腾,发现这个 Container Registry,有一年的免费试用期,但是免费
  317. </div>
  318. </a>
  319. <div class="index-btm post-metas">
  320. <div class="post-meta mr-3">
  321. <i class="iconfont icon-date"></i>
  322. <time datetime="2024-01-09 13:55" pubdate>
  323. 2024-01-09
  324. </time>
  325. </div>
  326. <div class="post-meta">
  327. <i class="iconfont icon-tags"></i>
  328. <a href="/tags/openai/">#openai</a>
  329. </div>
  330. </div>
  331. </article>
  332. </div>
  333. <div class="row mx-auto index-card">
  334. <div class="col-12 col-md-4 m-auto index-img">
  335. <a href="/Running-Qwen-on-the-Win10-platform-with-6GB-of-video-memory" target="_self">
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  337. </a>
  338. </div>
  339. <article class="col-12 col-md-8 mx-auto index-info">
  340. <h2 class="index-header">
  341. <a href="/Running-Qwen-on-the-Win10-platform-with-6GB-of-video-memory" target="_self">
  342. 【记录】win10平台6G显存运行Qwen-1.8B
  343. </a>
  344. </h2>
  345. <a class="index-excerpt " href="/Running-Qwen-on-the-Win10-platform-with-6GB-of-video-memory" target="_self">
  346. <div>
  347. Llama.cpp 能 CPU &amp; GPU 环境混合推理,这里记录一下在 windows10 平台上运行 Qwen-1.8B 的过程,显卡是 1660Ti 。 准备模型 安装conda Tun模式(管理员权限) 1234567conda create -n llamaConvert python=3.10 git -c conda-forgeconda activate llamaCo
  348. </div>
  349. </a>
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  351. <div class="post-meta mr-3">
  352. <i class="iconfont icon-date"></i>
  353. <time datetime="2024-01-01 11:11" pubdate>
  354. 2024-01-01
  355. </time>
  356. </div>
  357. <div class="post-meta">
  358. <i class="iconfont icon-tags"></i>
  359. <a href="/tags/llama/">#llama</a>
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  371. <h2 class="index-header">
  372. <a href="/Lightweight-personal-navigation-page-Flare" target="_self">
  373. 【记录】轻量个人导航页面 Flare
  374. </a>
  375. </h2>
  376. <a class="index-excerpt " href="/Lightweight-personal-navigation-page-Flare" target="_self">
  377. <div>
  378. Flare 是一款轻量、快速、美观的个人导航页面,适用于 HomeLab 或其他注重私密的场景。 反向代理服务 访问 https://flare.limour.top/editor 进行书签编辑 123mkdir -p ~/app/flare &amp;&amp; cd ~/app/flare &amp;&amp; nano docker-compose.ymlsudo docker-comp
  379. </div>
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  384. <time datetime="2024-01-01 01:18" pubdate>
  385. 2024-01-01
  386. </time>
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  388. <div class="post-meta">
  389. <i class="iconfont icon-tags"></i>
  390. <a href="/tags/docker/">#docker</a>
  391. <a href="/tags/ngpm/">#ngpm</a>
  392. <a href="/tags/homepage/">#homepage</a>
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  401. </a>
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  404. <h2 class="index-header">
  405. <a href="/Compile-Qwen-1.8B-Chat-using-MLC-LLM-on-Win" target="_self">
  406. 【记录】Win10平台使用MLC-LLM编译Qwen-1.8B-Chat
  407. </a>
  408. </h2>
  409. <a class="index-excerpt " href="/Compile-Qwen-1.8B-Chat-using-MLC-LLM-on-Win" target="_self">
  410. <div>
  411. MLC-LLM 是一种大模型高性能通用部署解决方案,可以通过预编译加速使用本机API原生部署任何大型语言模型。该项目的使命是利用ML编译技术,使每个人都能在其设备上本地开发、优化和部署AI模型。 Qwen-1.8B 是阿里云研发的通义千问大模型系列的18亿参数规模的模型。在Qwen-1.8B的基础上,使用对齐机制打造了基于大语言模型的AI助手 Qwen-1.8B-Chat。 配置环境 安装con
  412. </div>
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  418. 2023-12-09
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  422. <i class="iconfont icon-tags"></i>
  423. <a href="/tags/llama/">#llama</a>
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  432. </a>
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  434. <article class="col-12 col-md-8 mx-auto index-info">
  435. <h2 class="index-header">
  436. <a href="/Equivalent-operations-in-surgical-knot-tying" target="_self">
  437. 【探索】外科打结法中的等价操作
  438. </a>
  439. </h2>
  440. <a class="index-excerpt " href="/Equivalent-operations-in-surgical-knot-tying" target="_self">
  441. <div>
  442. 手术中的止血和缝合,均需要进行结扎,而结扎是否牢固,又与打结有密切关系,结一定要打得牢固,不能松动、滑脱。 常用的结扣是方结,结扎后极为牢固,在手术中最常用。而打方结时,手法顺序错误就容易打成假结或滑结。因此这里将探讨基础打结手法的等价性,帮助快速理解不同手法所成结的本质。 除不易混淆的外科结外,无论是单手打结还是持钳打结,均由基础动作组合而成,基础动作所成的结都对应纽结理论中的三叶结。三叶结有两
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