Quick Start Guide to Large Language Models

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ThePractical,Step-by-StepGuidetoUsingLLMsatScaleinProjectsandProductsLargeLanguageModels(LLMs)likeChatGPTaredemonstratingbreathtakingcapabilities,buttheirsizeandcomplexityhavedeterredmanypractitionersfromapplyingthem.InQuickStartGuidetoLargeLanguageModels,pioneeringdatascientistandAIentrepreneurSinanOzdemirclearsawaythoseobstaclesandprovidesaguidetoworkingwith,integrating,anddeployingLLMstosolvepracticalproblems.Ozdemirbringstogetherallyouneedtogetstarted,evenifyouhavenodirectexperiencewithLLMs:step-by-stepinstructions,bestpractices,real-worldcasestudies,hands-onexercises,andmore.Alongtheway,hesharesinsightsintoLLMs’innerworkingstohelpyouoptimizemodelchoice,dataformats,parameters,andperformance.You’llfindevenmoreresourcesonthecompanionwebsite,includingsampledatasetsandcodeforworkingwithopen-andclosed-sourceLLMssuchasthosefromOpenAI(GPT-4andChatGPT),Google(BERT,T5,andBard),EleutherAI(GPT-JandGPT-Neo),Cohere(theCommandfamily),andMeta(BARTandtheLLaMAfamily).Learnkeyconcepts:pre-training,transferlearning,fine-tuning,attention,embeddings,tokenization,andmoreUseAPIsandPythontofine-tuneandcustomizeLLMsforyourrequirementsBuildacompleteneural/semanticinformationretrievalsystemandattachtoconversationalLLMsforretrieval-augmentedgenerationMasteradvancedpromptengineeringtechniqueslikeoutputstructuring,chain-ofthought,andsemanticfew-shotpromptingCustomizeLLMembeddingstobuildacompleterecommendationenginefromscratchwithuserdataConstructandfine-tunemultimodalTransformerarchitecturesusingopensourceLLMsAlignLLMsusingReinforcementLearningfromHumanandAIFeedback(RLHF/RLAIF)Deploypromptsandcustomfine-tunedLLMstothecloudwithscalabilityandevaluationpipelinesinmind“Bybalancingthepotentialofbothopen-andclosed-sourcemodels,QuickStartGuidetoLargeLanguageModelsstandsasacomprehensiveguidetounderstandingandusingLLMs,bridgingthegapbetweentheoreticalconceptsandpracticalapplication.“--GiadaPistilli,PrincipalEthicistatHuggingFace“Arefreshingandinspiringresource.Jam-packedwithpracticalguidanceandclearexplanationsthatleaveyousmarteraboutthisincrediblenewfield.“--PeteHuang,authorofTheNeuronRegisteryourbookforconvenientaccesstodownloads,updates,and/orcorrectionsastheybecomeavailable.Seeinsidebookfordetails.


GOOGLE REAL TRAINING TRANSFERLEARNING START STEP LANGUAGE T5 QUICK MODELS embeddings UPDATES