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Title: GitHub - planetmicro/AI-Interview-Code: LLM大模型(重点)以及搜广推等 AI 算法中手写的面试题,(非 LeetCode),比如 Self-Attention, AUC等,一般比 LeetCode 更考察一个人的综合能力,又更贴近业务和基础知识一点 · GitHub

Open Graph Title: GitHub - planetmicro/AI-Interview-Code: LLM大模型(重点)以及搜广推等 AI 算法中手写的面试题,(非 LeetCode),比如 Self-Attention, AUC等,一般比 LeetCode 更考察一个人的综合能力,又更贴近业务和基础知识一点

X Title: GitHub - planetmicro/AI-Interview-Code: LLM大模型(重点)以及搜广推等 AI 算法中手写的面试题,(非 LeetCode),比如 Self-Attention, AUC等,一般比 LeetCode 更考察一个人的综合能力,又更贴近业务和基础知识一点

Description: LLM大模型(重点)以及搜广推等 AI 算法中手写的面试题,(非 LeetCode),比如 Self-Attention, AUC等,一般比 LeetCode 更考察一个人的综合能力,又更贴近业务和基础知识一点 - planetmicro/AI-Interview-Code

Open Graph Description: LLM大模型(重点)以及搜广推等 AI 算法中手写的面试题,(非 LeetCode),比如 Self-Attention, AUC等,一般比 LeetCode 更考察一个人的综合能力,又更贴近业务和基础知识一点 - planetmicro/AI-Interview-Code

X Description: LLM大模型(重点)以及搜广推等 AI 算法中手写的面试题,(非 LeetCode),比如 Self-Attention, AUC等,一般比 LeetCode 更考察一个人的综合能力,又更贴近业务和基础知识一点 - planetmicro/AI-Interview-Code

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og:image:altLLM大模型(重点)以及搜广推等 AI 算法中手写的面试题,(非 LeetCode),比如 Self-Attention, AUC等,一般比 LeetCode 更考察一个人的综合能力,又更贴近业务和基础知识一点 - planetmicro/AI-Interview-Code
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https://github.com/planetmicro/AI-Interview-Code#目录
手写 Self-Attention 的四重境界https://bruceyuan.com/hands-on-code/from-self-attention-to-multi-head-self-attention.html#%E9%9D%A2%E8%AF%95%E5%86%99%E6%B3%95-%E5%AE%8C%E6%95%B4%E7%89%88-%E6%B3%A8%E6%84%8F%E6%B3%A8%E9%87%8A
https://www.bilibili.com/video/BV19YbFeHETz/
https://www.youtube.com/watch?v=d_jwwnYCzIg
手写 Multi-Head Self-Attentionhttps://bruceyuan.com/hands-on-code/from-self-attention-to-multi-head-self-attention.html#%E9%9D%A2%E8%AF%95%E5%86%99%E6%B3%95-%E5%AE%8C%E6%95%B4%E7%89%88-%E6%B3%A8%E6%84%8F%E6%B3%A8%E9%87%8A
https://www.bilibili.com/video/BV19mxdeBEbu/
https://www.youtube.com/watch?v=SsWxatYLB-s
手写大模型组件之Group Query Attention,从 MHA -> MQA -> GQAhttps://bruceyuan.com/hands-on-code/hands-on-group-query-attention-and-multi-query-attention.html
https://www.bilibili.com/video/BV1ZmqpYfEGY/
https://www.youtube.com/watch?v=1jBW7qcyd7A
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LLM 大模型训练-推理显存占用分析https://bruceyuan.com/post/llm-train-infer-memoery-usage-calculation.html
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