├── .gitignore
├── LICENSE
├── README.md
└── src
├── hands-on-causal-lm-decoder-transformers-decoder.ipynb
├── hands-on-lora.ipynb
├── hands-on-multi-head-self-attention.ipynb
└── hands-on-self-attention.ipynb
/.gitignore:
--------------------------------------------------------------------------------
1 | # Byte-compiled / optimized / DLL files
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4 | *$py.class
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80 |
81 | # IPython
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84 |
85 | # pyenv
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88 | # .python-version
89 |
90 | # pipenv
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92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies
93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not
94 | # install all needed dependencies.
95 | #Pipfile.lock
96 |
97 | # poetry
98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
99 | # This is especially recommended for binary packages to ensure reproducibility, and is more
100 | # commonly ignored for libraries.
101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
102 | #poetry.lock
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106 | #pdm.lock
107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
108 | # in version control.
109 | # https://pdm.fming.dev/latest/usage/project/#working-with-version-control
110 | .pdm.toml
111 | .pdm-python
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113 |
114 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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157 | # PyCharm
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159 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
160 | # and can be added to the global gitignore or merged into this file. For a more nuclear
161 | # option (not recommended) you can uncomment the following to ignore the entire idea folder.
162 | #.idea/
163 |
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/README.md:
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1 | # AI-Interview-Code
2 | AI 大模型相关算法中手写的面试题,(非 LeetCode),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
3 |
4 | - 欢迎关注我的博客:[chaofa用代码打点酱油](https://bruceyuan.com/) ,内容一般会首先更新到博客上面,并且有更好的阅读体验。
5 | - 当前也欢迎关注同名公众号 **[chaofa用代码打点酱油](https://mp.weixin.qq.com/s/WxLbKvW4_9g0ajQ0wGRruQ)**,这样可以获得订阅更新
6 |
7 |
8 | ## 目录
9 |
10 | | 题目 | 难度 | 知识点 | 文字解读 | 视频解读 |
11 | | ---- | ---- | ---- | ---- | ---- |
12 | | 手写 Self-Attention | ⭐⭐⭐ | 注意力机制 | [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) |
13 | | 手写 Multi-Head Self-Attention | ⭐⭐⭐ | 注意力机制 | [手写 Multi-Head Self-Attention](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/BV19mxdeBEbu/)
[](https://www.youtube.com/watch?v=SsWxatYLB-s) |
14 | | 手写 Group-Query Attention | ⭐⭐⭐ | 注意力机制 | [手写大模型组件之Group Query Attention,从 MHA -> MQA -> GQA](https://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) |
15 | | 手写 Transformer Decoder(Causal Language Model, LM)| ⭐⭐⭐⭐ | Transformer 架构 | [手写 Transformer Decoder](https://bruceyuan.com/hands-on-code/hands-on-causallm-decoder.html) | [](https://www.bilibili.com/video/BV1Nh1QYCEsS/)
[](https://www.youtube.com/watch?v=yzEotGJaQ74) |
16 | | 计算 LLM (Decoder) 模型的参数量 | ⭐⭐⭐ | 模型参数量 | TODO | [](https://www.bilibili.com/video/BV1Zw4ue2ELg/)
[](https://www.youtube.com/watch?v=q5quYPt2z5s) |
17 | | LLM 模型训练推理显存占用预估 | ⭐⭐⭐⭐ | 显存占用 | [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) | |
18 | | 手写 AUC | ⭐⭐ | 模型评估 | TODO | |
19 | | 手写 KMeans | ⭐⭐⭐⭐⭐ | 聚类 | TODO | |
20 | | 手写 线性回归 | ⭐⭐⭐⭐⭐ | 线性回归 | TODO | |
21 | | 手写 BPE 分词器 | ⭐⭐⭐⭐⭐ | 分词 | TODO | |
22 | | 手写 LayerNorm | ⭐⭐ | 归一化 | TODO | |
23 | | 手写 BatchNorm | ⭐⭐ | 归一化 | TODO | |
24 | | 手写 Softmax | ⭐⭐ | 激活函数 | TODO | |
25 |
26 | ## 一般不会考的
27 | | 题目 | 难度 | 知识点 | 文字解读 | 视频解读 |
28 | | ---- | ---- | ---- | ---- | ---- |
29 | | 手写 LoRA | ⭐⭐⭐⭐⭐ | 目的是为了深入了解 LoRA | [LoRA 原理和 PyTorch 代码实现](https://bruceyuan.com/hands-on-code/hands-on-lora.html)
[](https://openbayes.com/console/bbruceyuan/containers/OPg9Oo99ET6) | [](https://www.bilibili.com/video/BV1fHmkYyE2w/)
|
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/src/hands-on-causal-lm-decoder-transformers-decoder.ipynb:
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19 |
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17 | "nbformat_minor": 2
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1 | {
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1 | {
2 | "cells": [
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