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<?xml version="1.0" encoding="utf-8"?>
<feed xmlns="http://www.w3.org/2005/Atom">
<title>iMountTai's Blog</title>
<subtitle>AI, NLP, LLM 学习笔记</subtitle>
<link href="https://imounttai.github.io/atom.xml" rel="self"/>
<link href="https://imounttai.github.io/"/>
<updated>2026-07-04T01:49:20.925Z</updated>
<id>https://imounttai.github.io/</id>
<author>
<name>iMountTai</name>
</author>
<generator uri="https://hexo.io/">Hexo</generator>
<entry>
<title>Codex CLI 接入 Chrome：配置 @Chrome 的完整步骤</title>
<link href="https://imounttai.github.io/codex-cli-chrome.html"/>
<id>https://imounttai.github.io/codex-cli-chrome.html</id>
<published>2026-07-03T16:00:00.000Z</published>
<updated>2026-07-04T01:49:20.925Z</updated>
<summary type="html">Codex CLI 接入 Chrome Extension 的配置与验证步骤。</summary>
<category term="工程实践" scheme="https://imounttai.github.io/categories/%E5%B7%A5%E7%A8%8B%E5%AE%9E%E8%B7%B5/"/>
<category term="Codex" scheme="https://imounttai.github.io/tags/Codex/"/>
<category term="Chrome" scheme="https://imounttai.github.io/tags/Chrome/"/>
<category term="AI Coding" scheme="https://imounttai.github.io/tags/AI-Coding/"/>
</entry>
<entry>
<title>DeepSpeed-Chat Llama/Llama-2</title>
<link href="https://imounttai.github.io/deepspeed-chat.html"/>
<id>https://imounttai.github.io/deepspeed-chat.html</id>
<published>2023-08-31T13:58:05.000Z</published>
<updated>2023-09-03T15:18:59.424Z</updated>
<summary type="html"><p>blog<a href="https://github.com/microsoft/DeepSpeed/blob/master/blogs/deepspeed-chat/ds-chat-release-8-31/README.md">DeepSpeed-Chat for</summary>
<category term="人工智能" scheme="https://imounttai.github.io/categories/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD/"/>
<category term="NLP" scheme="https://imounttai.github.io/categories/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD/NLP/"/>
<category term="LLM" scheme="https://imounttai.github.io/tags/LLM/"/>
<category term="Pre-training" scheme="https://imounttai.github.io/tags/Pre-training/"/>
</entry>
<entry>
<title>LOMO：低资源下的大语言模型全参数微调</title>
<link href="https://imounttai.github.io/lomo.html"/>
<id>https://imounttai.github.io/lomo.html</id>
<published>2023-07-09T08:15:15.000Z</published>
<updated>2026-07-04T02:07:16.219Z</updated>
<summary type="html">阅读论文 FULL PARAMETER FINE-TUNING FOR LARGE LANGUAGE MODELS WITH LIMITED RESOURCES，整理 LOMO 优化器的核心思路、显存收益和实验结论。</summary>
<category term="人工智能" scheme="https://imounttai.github.io/categories/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD/"/>
<category term="NLP" scheme="https://imounttai.github.io/categories/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD/NLP/"/>
<category term="LLM" scheme="https://imounttai.github.io/tags/LLM/"/>
<category term="Fine-tuning" scheme="https://imounttai.github.io/tags/Fine-tuning/"/>
</entry>
<entry>
<title>QLoRA-Efficient Finetuning of Quantized LLMs</title>
<link href="https://imounttai.github.io/qlora.html"/>
<id>https://imounttai.github.io/qlora.html</id>
<published>2023-05-28T07:35:21.000Z</published>
<updated>2023-09-03T15:10:25.929Z</updated>
<summary type="html">高效精调</summary>
<category term="人工智能" scheme="https://imounttai.github.io/categories/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD/"/>
<category term="NLP" scheme="https://imounttai.github.io/categories/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD/NLP/"/>
<category term="LLM" scheme="https://imounttai.github.io/tags/LLM/"/>
<category term="Pre-training" scheme="https://imounttai.github.io/tags/Pre-training/"/>
</entry>
<entry>
<title>deepspeed</title>
<link href="https://imounttai.github.io/deepspeed.html"/>
<id>https://imounttai.github.io/deepspeed.html</id>
<published>2023-03-11T14:27:04.000Z</published>
<updated>2023-09-03T15:31:07.940Z</updated>
<summary type="html"><p>deepspeed config</summary>
<category term="人工智能" scheme="https://imounttai.github.io/categories/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD/"/>
<category term="NLP" scheme="https://imounttai.github.io/categories/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD/NLP/"/>
<category term="LLM" scheme="https://imounttai.github.io/tags/LLM/"/>
<category term="chatgpt" scheme="https://imounttai.github.io/tags/chatgpt/"/>
</entry>
<entry>
<title>MobileBERT a Compact Task-Agnostic BERT for Resource-Limited Devices</title>
<link href="https://imounttai.github.io/mobilebert.html"/>
<id>https://imounttai.github.io/mobilebert.html</id>
<published>2022-08-07T06:38:45.000Z</published>
<updated>2023-09-03T15:10:54.262Z</updated>
<summary type="html"><p>论文<br><a href="https://arxiv.org/pdf/2004.02984.pdf">MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices</a></p>
<h1</summary>
<category term="人工智能" scheme="https://imounttai.github.io/categories/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD/"/>
<category term="NLP" scheme="https://imounttai.github.io/categories/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD/NLP/"/>
<category term="知识蒸馏" scheme="https://imounttai.github.io/tags/%E7%9F%A5%E8%AF%86%E8%92%B8%E9%A6%8F/"/>
<category term="BERT" scheme="https://imounttai.github.io/tags/BERT/"/>
<category term="KD" scheme="https://imounttai.github.io/tags/KD/"/>
</entry>
<entry>
<title>Distilling Task-Specific Knowledge from BERT into Simple Neural Networks</title>
<link href="https://imounttai.github.io/bert-to-lstm.html"/>
<id>https://imounttai.github.io/bert-to-lstm.html</id>
<published>2022-07-26T02:17:19.000Z</published>
<updated>2023-08-27T08:25:27.605Z</updated>
<summary type="html"><p>论文<br><a href="https://arxiv.org/pdf/1903.12136.pdf">Distilling Task-Specific Knowledge from BERT into Simple Neural</summary>
<category term="人工智能" scheme="https://imounttai.github.io/categories/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD/"/>
<category term="NLP" scheme="https://imounttai.github.io/categories/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD/NLP/"/>
<category term="知识蒸馏" scheme="https://imounttai.github.io/tags/%E7%9F%A5%E8%AF%86%E8%92%B8%E9%A6%8F/"/>
<category term="BERT" scheme="https://imounttai.github.io/tags/BERT/"/>
<category term="KD" scheme="https://imounttai.github.io/tags/KD/"/>
</entry>
</feed>