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Title: GitHub - flamecodezz/llm-action: 本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）

Open Graph Title: GitHub - flamecodezz/llm-action: 本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）

X Title: GitHub - flamecodezz/llm-action: 本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）

Description: 本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）. Contribute to flamecodezz/llm-action development by creating an account on GitHub.

Open Graph Description: 本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）. Contribute to flamecodezz/llm-action development by creating an account on GitHub.

X Description: 本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）. Contribute to flamecodezz/llm-action development by creating an account on GitHub.

Opengraph URL: https://github.com/flamecodezz/llm-action

X: @github

direct link

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AI基础设施https://patch-diff.githubusercontent.com/flamecodezz/llm-action#ai%E5%9F%BA%E7%A1%80%E8%AE%BE%E6%96%BD
AI加速卡https://patch-diff.githubusercontent.com/flamecodezz/llm-action#ai%E5%8A%A0%E9%80%9F%E5%8D%A1
AI集群网络通信https://patch-diff.githubusercontent.com/flamecodezz/llm-action#ai%E9%9B%86%E7%BE%A4%E7%BD%91%E7%BB%9C%E9%80%9A%E4%BF%A1
LLMOpshttps://patch-diff.githubusercontent.com/flamecodezz/llm-action#llmops
LLM生态相关技术https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm%E7%94%9F%E6%80%81%E7%9B%B8%E5%85%B3%E6%8A%80%E6%9C%AF
LLM面试题https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm%E9%9D%A2%E8%AF%95%E9%A2%98
服务器基础环境安装及常用工具https://patch-diff.githubusercontent.com/flamecodezz/llm-action#%E6%9C%8D%E5%8A%A1%E5%99%A8%E5%9F%BA%E7%A1%80%E7%8E%AF%E5%A2%83%E5%AE%89%E8%A3%85%E5%8F%8A%E5%B8%B8%E7%94%A8%E5%B7%A5%E5%85%B7
LLM学习交流群https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm%E5%AD%A6%E4%B9%A0%E4%BA%A4%E6%B5%81%E7%BE%A4
微信公众号https://patch-diff.githubusercontent.com/flamecodezz/llm-action#%E5%BE%AE%E4%BF%A1%E5%85%AC%E4%BC%97%E5%8F%B7
Star Historyhttps://patch-diff.githubusercontent.com/flamecodezz/llm-action#star-history
AI工程化课程推荐https://patch-diff.githubusercontent.com/flamecodezz/llm-action#ai%E5%B7%A5%E7%A8%8B%E5%8C%96%E8%AF%BE%E7%A8%8B%E6%8E%A8%E8%8D%90
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm训练
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm训练实战
从0到1复现斯坦福羊驼（Stanford Alpaca 7B）https://zhuanlan.zhihu.com/p/618321077
配套代码https://github.com/liguodongiot/llm-action/tree/main/llm-train/alpaca
足够惊艳，使用Alpaca-Lora基于LLaMA(7B)二十分钟完成微调，效果比肩斯坦福羊驼https://zhuanlan.zhihu.com/p/619426866
使用 LoRA 技术对 LLaMA 65B 大模型进行微调及推理https://zhuanlan.zhihu.com/p/632492604
配套代码https://github.com/liguodongiot/llm-action/tree/main/llm-train/alpaca-lora
基于LLaMA-7B/Bloomz-7B1-mt复现开源中文对话大模型BELLE及GPTQ量化https://zhuanlan.zhihu.com/p/618876472
BELLE(LLaMA-7B/Bloomz-7B1-mt)大模型使用GPTQ量化后推理性能测试https://zhuanlan.zhihu.com/p/621128368
从0到1基于ChatGLM-6B使用LoRA进行参数高效微调https://zhuanlan.zhihu.com/p/621793987
配套代码https://github.com/liguodongiot/llm-action/tree/main/train/chatglm-lora
使用DeepSpeed/P-Tuning v2对ChatGLM-6B进行微调https://zhuanlan.zhihu.com/p/622351059
配套代码https://github.com/liguodongiot/llm-action/tree/main/train/chatglm
大模型也内卷，Vicuna训练及推理指南，效果碾压斯坦福羊驼https://zhuanlan.zhihu.com/p/624012908
一键式 RLHF 训练 DeepSpeed Chat（一）：理论篇https://zhuanlan.zhihu.com/p/626159553
一键式 RLHF 训练 DeepSpeed Chat（二）：实践篇https://zhuanlan.zhihu.com/p/626214655
配套代码https://github.com/liguodongiot/llm-action/tree/main/train/deepspeedchat
大杀器，多模态大模型MiniGPT-4入坑指南https://zhuanlan.zhihu.com/p/627671257
中文LLaMA&Alpaca大语言模型词表扩充+预训练+指令精调https://zhuanlan.zhihu.com/p/631360711
配套代码https://github.com/liguodongiot/llm-action/tree/main/train/chinese-llama-alpaca
高效微调技术QLoRA实战，基于LLaMA-65B微调仅需48G显存，真香https://zhuanlan.zhihu.com/p/636644164
配套代码https://github.com/liguodongiot/llm-action/tree/main/train/qlora
突破内存瓶颈，使用 GaLore 一张4090消费级显卡也能预训练LLaMA-7Bhttps://zhuanlan.zhihu.com/p/686686751
配套代码https://github.com/liguodongiot/llm-action/blob/main/train/galore/torchrun_main.py
⬆ 一键返回目录https://patch-diff.githubusercontent.com/flamecodezz/llm-action#%E7%9B%AE%E5%BD%95
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm微调技术原理
https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main/pic/llm/train/sft/peft%E6%96%B9%E6%B3%95.jpg
大模型参数高效微调技术原理综述（一）-背景、参数高效微调简介https://zhuanlan.zhihu.com/p/635152813
大模型参数高效微调技术原理综述（二）-BitFit、Prefix Tuning、Prompt Tuninghttps://zhuanlan.zhihu.com/p/635686756
大模型参数高效微调技术原理综述（三）-P-Tuning、P-Tuning v2https://zhuanlan.zhihu.com/p/635848732
大模型参数高效微调技术原理综述（四）-Adapter Tuning及其变体https://zhuanlan.zhihu.com/p/636038478
大模型参数高效微调技术原理综述（五）-LoRA、AdaLoRA、QLoRAhttps://zhuanlan.zhihu.com/p/636215898
大模型参数高效微调技术原理综述（六）-MAM Adapter、UniPELThttps://zhuanlan.zhihu.com/p/636362246
大模型参数高效微调技术原理综述（七）-最佳实践、总结https://zhuanlan.zhihu.com/p/649755252
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm微调实战
大模型参数高效微调技术实战（一）-PEFT概述及环境搭建https://zhuanlan.zhihu.com/p/651744834
大模型参数高效微调技术实战（二）-Prompt Tuninghttps://zhuanlan.zhihu.com/p/646748939
配套代码https://github.com/liguodongiot/llm-action/blob/main/llm-action/peft/clm/peft_prompt_tuning_clm.ipynb
大模型参数高效微调技术实战（三）-P-Tuninghttps://zhuanlan.zhihu.com/p/646876256
配套代码https://github.com/liguodongiot/llm-action/blob/main/llm-action/peft/clm/peft_p_tuning_clm.ipynb
大模型参数高效微调技术实战（四）-Prefix Tuning / P-Tuning v2https://zhuanlan.zhihu.com/p/648156780
配套代码https://github.com/liguodongiot/llm-action/blob/main/llm-action/peft/clm/peft_p_tuning_v2_clm.ipynb
大模型参数高效微调技术实战（五）-LoRAhttps://zhuanlan.zhihu.com/p/649315197
配套代码https://github.com/liguodongiot/llm-action/blob/main/llm-action/peft/clm/peft_lora_clm.ipynb
大模型参数高效微调技术实战（六）-IA3https://zhuanlan.zhihu.com/p/649707359
配套代码https://github.com/liguodongiot/llm-action/blob/main/llm-action/peft/clm/peft_ia3_clm.ipynb
大模型微调实战（七）-基于LoRA微调多模态大模型https://zhuanlan.zhihu.com/p/670048482
配套代码https://github.com/liguodongiot/llm-action/blob/main/llm-action/peft/multimodal/blip2_lora_int8_fine_tune.py
大模型微调实战（八）-使用INT8/FP4/NF4微调大模型https://zhuanlan.zhihu.com/p/670116171
配套代码https://github.com/liguodongiot/llm-action/blob/main/llm-action/peft/multimodal/finetune_bloom_bnb_peft.ipynb
⬆ 一键返回目录https://patch-diff.githubusercontent.com/flamecodezz/llm-action#%E7%9B%AE%E5%BD%95
LLM分布式训练并行技术https://github.com/liguodongiot/llm-action/tree/main/docs/llm-base/distribution-parallelism
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm分布式训练并行技术
大模型分布式训练并行技术（一）-概述https://zhuanlan.zhihu.com/p/598714869
大模型分布式训练并行技术（二）-数据并行https://zhuanlan.zhihu.com/p/650002268
大模型分布式训练并行技术（三）-流水线并行https://zhuanlan.zhihu.com/p/653860567
大模型分布式训练并行技术（四）-张量并行https://zhuanlan.zhihu.com/p/657921100
大模型分布式训练并行技术（五）-序列并行https://zhuanlan.zhihu.com/p/659792351
大模型分布式训练并行技术（六）-多维混合并行https://zhuanlan.zhihu.com/p/661279318
大模型分布式训练并行技术（七）-自动并行https://zhuanlan.zhihu.com/p/662517647
大模型分布式训练并行技术（八）-MOE并行https://zhuanlan.zhihu.com/p/662518387
大模型分布式训练并行技术（九）-总结https://zhuanlan.zhihu.com/p/667051845
⬆ 一键返回目录https://patch-diff.githubusercontent.com/flamecodezz/llm-action#%E7%9B%AE%E5%BD%95
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#分布式ai框架
PyTorchhttps://github.com/liguodongiot/llm-action/tree/main/train/pytorch/
Megatron-LMhttps://github.com/liguodongiot/llm-action/tree/main/train/megatron
基于Megatron-LM从0到1完成GPT2模型预训练、模型评估及推理https://juejin.cn/post/7259682893648724029
DeepSpeedhttps://github.com/liguodongiot/llm-action/tree/main/train/deepspeed
Megatron-DeepSpeedhttps://github.com/liguodongiot/llm-action/tree/main/train/megatron-deepspeed
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#分布式训练网络通信
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm训练优化技术
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm对齐技术
⬆ 一键返回目录https://patch-diff.githubusercontent.com/flamecodezz/llm-action#%E7%9B%AE%E5%BD%95
LLM推理https://github.com/liguodongiot/llm-action/tree/main/inference
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm推理
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm推理框架
大模型推理框架概述https://www.zhihu.com/question/625415776/answer/3243562246
大模型的好伙伴，浅析推理加速引擎FasterTransformerhttps://zhuanlan.zhihu.com/p/626008090
模型推理服务化框架Triton保姆式教程（一）：快速入门https://zhuanlan.zhihu.com/p/629336492
模型推理服务化框架Triton保姆式教程（二）：架构解析https://zhuanlan.zhihu.com/p/634143650
模型推理服务化框架Triton保姆式教程（三）：开发实践https://zhuanlan.zhihu.com/p/634444666
TensorRT-LLM保姆级教程（一）-快速入门https://zhuanlan.zhihu.com/p/666849728
TensorRT-LLM保姆级教程（二）-离线环境搭建、模型量化及推理https://zhuanlan.zhihu.com/p/667572720
TensorRT-LLM保姆级教程（三）-使用Triton推理服务框架部署模型https://juejin.cn/post/7398122968200593419
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm推理优化技术
LLM推理优化技术-概述https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
大模型推理优化技术-KV Cachehttps://www.zhihu.com/question/653658936/answer/3569365986
大模型推理服务调度优化技术-Continuous batchinghttps://zhuanlan.zhihu.com/p/719610083
大模型低显存推理优化-Offload技术https://juejin.cn/post/7405158045628596224
大模型推理优化技术-KV Cache量化https://juejin.cn/post/7420231738558627874
大模型推理优化技术-KV Cache优化方法综述https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm压缩
LLM量化https://github.com/liguodongiot/llm-action/tree/main/model-compression/quantization
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm量化
大模型量化概述https://www.zhihu.com/question/627484732/answer/3261671478
大模型量化感知训练技术原理：LLM-QAThttps://zhuanlan.zhihu.com/p/647589650
大模型量化感知微调技术原理：QLoRAhttps://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
大模型量化技术原理：GPTQ、LLM.int8()https://zhuanlan.zhihu.com/p/680212402
大模型量化技术原理：SmoothQuanthttps://www.zhihu.com/question/576376372/answer/3388402085
大模型量化技术原理：AWQ、AutoAWQhttps://zhuanlan.zhihu.com/p/681578090
大模型量化技术原理：SpQRhttps://zhuanlan.zhihu.com/p/682871823
大模型量化技术原理：ZeroQuant系列https://zhuanlan.zhihu.com/p/683813769
大模型量化技术原理：FP8https://www.zhihu.com/question/658712811/answer/3596678896
大模型量化技术原理：FP6https://juejin.cn/post/7412893752090853386
大模型量化技术原理：KIVI、IntactKV、KVQuanthttps://juejin.cn/post/7420231738558627874
大模型量化技术原理：Atom、QuaRothttps://juejin.cn/post/7424334647570513972
大模型量化技术原理：QoQ量化及QServe推理服务系统https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
大模型量化技术原理：FP4https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
大模型量化技术原理：总结https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm剪枝
万字长文谈深度神经网络剪枝综述https://zhuanlan.zhihu.com/p/692858636
大模型剪枝技术原理：概述https://www.zhihu.com/question/652126515/answer/3457652467
大模型剪枝技术原理：LLM-Pruner、SliceGPThttps://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
大模型剪枝技术原理：SparseGPT、Wandahttps://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
大模型剪枝技术原理：总结https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm知识蒸馏
大模型知识蒸馏概述https://www.zhihu.com/question/625415893/answer/3243565375
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#低秩分解
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm测评
C-Evalhttps://github.com/liguodongiot/ceval
CMMLUhttps://github.com/liguodongiot/CMMLU
IFEval: Instruction Following Evalhttps://github.com/google-research/google-research/tree/master/instruction_following_eval
Paperhttps://arxiv.org/abs/2311.07911
SuperCLUEhttps://github.com/CLUEbenchmark/SuperCLUE
AGIEvalhttps://github.com/ruixiangcui/AGIEval/
OpenCompasshttps://github.com/open-compass/opencompass/blob/main/README_zh-CN.md
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm数据工程
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#预训练语料处理技术
https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main/pic/llm/train/pretrain/llm-pretrain-pipeline-v2.png
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm微调高效数据筛选技术
LLM微调高效数据筛选技术原理-DEITAhttps://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
LLM微调高效数据筛选技术原理-MoDShttps://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
LLM微调高效数据筛选技术原理-IFDhttps://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
LLM微调高效数据筛选技术原理-CaRhttps://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
LESS：仅选择5%有影响力的数据优于全量数据集进行目标指令微调https://zhuanlan.zhihu.com/p/686007325
LESS 实践：用少量的数据进行目标指令微调https://zhuanlan.zhihu.com/p/686687923
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#提示工程
LLM算法架构https://github.com/liguodongiot/llm-action/tree/main/docs/llm-base/ai-algo
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm算法架构
https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main/pic/llm/model/llm-famliy.jpg
大模型算法演进https://zhuanlan.zhihu.com/p/600016134
https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main/pic/llm/model/llm-timeline-v2.png
百川智能开源大模型baichuan-7B技术剖析https://www.zhihu.com/question/606757218/answer/3075464500
百川智能开源大模型baichuan-13B技术剖析https://www.zhihu.com/question/611507751/answer/3114988669
LLaMA3 技术剖析https://www.zhihu.com/question/653374932/answer/3470909634
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm应用开发
云原生向量数据库Milvus（一）-简述、系统架构及应用场景https://zhuanlan.zhihu.com/p/476025527
云原生向量数据库Milvus（二）-数据与索引的处理流程、索引类型及Schemahttps://zhuanlan.zhihu.com/p/477231485
关于大模型驱动的AI智能体Agent的一些思考https://zhuanlan.zhihu.com/p/651921120
LLM国产化适配https://github.com/liguodongiot/llm-action/tree/main/docs/llm_localization
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm国产化适配
大模型国产化适配1-华为昇腾AI全栈软硬件平台总结https://zhuanlan.zhihu.com/p/637918406
大模型国产化适配2-基于昇腾910使用ChatGLM-6B进行模型推理https://zhuanlan.zhihu.com/p/650730807
大模型国产化适配3-基于昇腾910使用ChatGLM-6B进行模型训练https://zhuanlan.zhihu.com/p/651324599
大模型国产化适配4-基于昇腾910使用LLaMA-13B进行多机多卡训练https://zhuanlan.zhihu.com/p/655902796
大模型国产化适配5-百度飞浆PaddleNLP大语言模型工具链总结https://zhuanlan.zhihu.com/p/665807431
大模型国产化适配6-基于昇腾910B快速验证ChatGLM3-6B/BaiChuan2-7B模型推理https://zhuanlan.zhihu.com/p/677799157
大模型国产化适配7-华为昇腾LLM落地可选解决方案（MindFormers、ModelLink、MindIE）https://zhuanlan.zhihu.com/p/692377206
MindIE 1.0.RC1 发布，华为昇腾终于推出了针对LLM的完整部署方案，结束小米加步枪时代https://www.zhihu.com/question/654472145/answer/3482521709
大模型国产化适配8-基于昇腾MindIE推理工具部署Qwen-72B实战（推理引擎、推理服务化）https://juejin.cn/post/7365879319598727180
大模型国产化适配9-LLM推理框架MindIE-Service性能基准测试https://zhuanlan.zhihu.com/p/704649189
大模型国产化适配10-快速迁移大模型到昇腾910B保姆级教程（Pytorch版）https://juejin.cn/post/7375351908896866323
大模型国产化适配11-LLM训练性能基准测试（昇腾910B3）https://juejin.cn/post/7380995631790964772
国产知名AI芯片厂商产品大揭秘-昇腾、海光、天数智芯...https://f46522gm22.feishu.cn/docx/PfWfdMKo8oXYN6xi7uycuhgFnKg
国内AI芯片厂商的计算平台大揭秘-昇腾、海光、天数智芯...https://f46522gm22.feishu.cn/docx/XnhcdXVDholUBpxYoMccS11Mnfc
【LLM国产化】量化技术在MindIE推理框架中的应用https://juejin.cn/post/7416723051377377316
⬆ 一键返回目录https://patch-diff.githubusercontent.com/flamecodezz/llm-action#%E7%9B%AE%E5%BD%95
AI编译器https://github.com/liguodongiot/llm-action/tree/main/ai-compiler
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#ai编译器
AI编译器技术剖析（一）-概述https://zhuanlan.zhihu.com/p/669347560
AI编译器技术剖析（二）-传统编译器https://zhuanlan.zhihu.com/p/671477784
AI编译器技术剖析（三）-树模型编译工具 Treelite 详解https://zhuanlan.zhihu.com/p/676723324
AI编译器技术剖析（四）-编译器前端https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
AI编译器技术剖析（五）-编译器后端https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
AI编译器技术剖析（六）-主流编译框架https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
AI编译器技术剖析（七）-深度学习模型编译优化https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
lleaves：使用 LLVM 编译梯度提升决策树将预测速度提升10+倍https://zhuanlan.zhihu.com/p/672584013
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#ai基础设施
AI 集群基础设施 NVMe SSD 详解https://zhuanlan.zhihu.com/p/672098336
AI 集群基础设施 InfiniBand 详解https://zhuanlan.zhihu.com/p/673903240
大模型训练基础设施：算力篇https://patch-diff.githubusercontent.com/flamecodezz/llm-action/blob/main
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#ai加速卡
AI芯片技术原理剖析（一）：国内外AI芯片概述https://zhuanlan.zhihu.com/p/667686665
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#ai集群
AI集群网络通信https://github.com/liguodongiot/llm-action/tree/main/docs/llm-base/network-communication
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#ai集群网络通信
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llmops
在 Kubernetes 上部署机器学习模型的指南https://zhuanlan.zhihu.com/p/676389726
使用 Kubernetes 部署机器学习模型的优势https://juejin.cn/post/7320513026188099619
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm生态相关技术
大模型词表扩充必备工具SentencePiecehttps://zhuanlan.zhihu.com/p/630696264
大模型实践总结https://www.zhihu.com/question/601594836/answer/3032763174
ChatGLM 和 ChatGPT 的技术区别在哪里？https://www.zhihu.com/question/604393963/answer/3061358152
现在为什么那么多人以清华大学的ChatGLM-6B为基座进行试验？https://www.zhihu.com/question/602504880/answer/3041965998
为什么很多新发布的大模型默认使用BF16而不是FP16？https://www.zhihu.com/question/616600181/answer/3195333332
大模型训练时ZeRO-2、ZeRO-3能否和Pipeline并行相结合？https://www.zhihu.com/question/652836990/answer/3468210626
一文详解模型权重存储新格式 Safetensorshttps://juejin.cn/post/7386360803039838235
一文搞懂大模型文件存储格式新宠GGUFhttps://juejin.cn/post/7408858126042726435
LLM面试题https://github.com/liguodongiot/llm-action/blob/main/llm-interview/README.md
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm面试题
大模型基础常见面试题https://github.com/liguodongiot/llm-action/blob/main/llm-interview/base.md
大模型算法常见面试题https://github.com/liguodongiot/llm-action/blob/main/llm-interview/llm-algo.md
大模型训练常见面试题https://github.com/liguodongiot/llm-action/blob/main/llm-interview/llm-train.md
大模型微调常见面试题https://github.com/liguodongiot/llm-action/blob/main/llm-interview/llm-ft.md
大模型评估常见面试题https://github.com/liguodongiot/llm-action/blob/main/llm-interview/llm-eval.md
大模型压缩常见面试题https://github.com/liguodongiot/llm-action/blob/main/llm-interview/llm-compress.md
大模型推理常见面试题https://github.com/liguodongiot/llm-action/blob/main/llm-interview/llm-inference.md
大模型应用常见面试题https://github.com/liguodongiot/llm-action/blob/main/llm-interview/llm-app.md
大模型综合性面试题https://github.com/liguodongiot/llm-action/blob/main/llm-interview/comprehensive.md
⬆ 一键返回目录https://patch-diff.githubusercontent.com/flamecodezz/llm-action#%E7%9B%AE%E5%BD%95
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#服务器基础环境安装及常用工具
英伟达A800加速卡常见软件包安装命令https://github.com/liguodongiot/llm-action/blob/main/docs/llm-base/a800-env-install.md
英伟达H800加速卡常见软件包安装命令https://github.com/liguodongiot/llm-action/blob/main/docs/llm-base/h800-env-install.md
昇腾910加速卡常见软件包安装命令https://github.com/liguodongiot/llm-action/blob/main/llm_localization/ascend910-env-install.md
Linux 常见命令大全https://juejin.cn/post/6992742028605915150
Conda 常用命令大全https://juejin.cn/post/7089093437223338015
Poetry 常用命令大全https://juejin.cn/post/6999405667261874183
Docker 常用命令大全https://juejin.cn/post/7016238524286861325
Docker Dockerfile 指令大全https://juejin.cn/post/7016595442062327844
Kubernetes 常用命令大全https://juejin.cn/post/7031201391553019911
集群环境 GPU 管理和监控工具 DCGM 常用命令大全https://github.com/liguodongiot/llm-action/blob/main/docs/llm-base/dcgmi.md
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#llm学习交流群
https://github.com/liguodongiot/llm-action/blob/main/pic/wx.jpg
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#微信公众号
https://github.com/liguodongiot/llm-action/blob/main/pic/wx-gzh.png
⬆ 一键返回目录https://patch-diff.githubusercontent.com/flamecodezz/llm-action#%E7%9B%AE%E5%BD%95
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#star-history
https://star-history.com/#liguodongiot/llm-action&Date
https://patch-diff.githubusercontent.com/flamecodezz/llm-action#ai工程化课程推荐
llm-resourcehttps://github.com/liguodongiot/llm-resource
ai-systemhttps://github.com/liguodongiot/ai-system
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www.zhihu.com/column/c_1456193767213043713https://www.zhihu.com/column/c_1456193767213043713
Readme https://patch-diff.githubusercontent.com/flamecodezz/llm-action#readme-ov-file
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