- Ubunjiniyela obusheshayo buvumela abathuthukisi ukuthi baguqule ama-LLM abe yizingxenye ezithembekile zezinhlelo zabo zokusebenza, ngale kokusetshenziswa kwengxoxo okuvamile.
- Izimiso ezimbili ziqondisa: imiyalelo ecacile neqondile, kanye nokunikeza imodeli "isikhathi sokucabanga" ngezinyathelo, izibonelo, kanye nokucabanga okuqondisiwe.
- Ama-LLM angafingqa, ahlukanise, ahumushe, akhiphe izinto, noma ondle ama-chatbot kanye nezinhlelo ze-RAG, uma nje isikhuthazo kanye nomongo kuklanywe kahle.
- Ukuphupha izinto ezingekho kanye nokulahlekelwa yinkumbulo kudinga ukuhlanganisa izikhuthazo eziqinile, ukuphathwa komlando, kanye nokuthola umongo wangaphandle ukuze kutholakale izixazululo eziphephile.
Ukuvela kwe- amamodeli olimi olukhulu (LLM) isishintshe ngokuphelele indlela esithuthukisa ngayo isofthiwe. Asisahleli nje kuphela: manje kufanele sifunde nokubuza izinto ngokuqondile ku- IA ukuze babhale ikhodi, imibhalo, izivivinyo, noma ngisho nezakhiwo eziphelele. Leli khono lokunikeza imiyalelo ecacile nephumelelayo laziwa ngokuthi ubunjiniyela obusheshayo bonjiniyela.
Uma uhlela ku PythonI-JavaScript, i-TypeScript, i-Java, i-Go, noma olunye ulimiUkwazi ubunjiniyela bokusheshisa kukuvumela ukuthi wenze i-LLM ibe yingxenye ebalulekile yezinhlelo zakho zokusebenza. Akusekho nje "ukukhuluma" nabantu. I-ChatGPT kuwebhusayithi”, kodwa kunalokho hlanganisa ama-API, sebenzisa amamodeli endawo, dala ama-chatbotAbasizi bekhodi, izinhlelo zokufingqa, kanye nokugeleza kwe-RAG okuhlanganisa idatha yakho namandla okukhiqiza emodeli.
Kuyini i-Prompt Engineering futhi kungani kufanele ukhathalele njengonjiniyela?
En esencia, la ubunjiniyela obusheshayo ikhono lokwenza bhala imiyalelo ecacile, eqondile, nehlelwe kahle ngemodeli ye I-AI ekhiqizayo Buyisela uhlobo olufanele lomkhiqizo oludingayo: ikhodi, umbhalo wobuchwepheshe, izifinyezo, ukuhlaziya, ukuguqulwa, noma izinqumo.
Un Unjiniyela Osheshayo (noma unjiniyela wemiyalelo) ngumuntu oklama, ahlole, futhi athuthukise lezo ziphakamiso. Ngokomongo wokuthuthukiswa kwesofthiwe, umsebenzi wabo ugxile ku Ukuxhumanisa ama-LLM nemikhiqizo yangempela: ababekhona ku- uhlelo, izinhlelo zokusekela ubuchwepheshe, amathuluzi angaphakathi amaqembu, ukuzenzekela kwamadokhumenti noma imibhobho yedatha esebenzisa i-AI.
Izeluleko ziyindlela abantu abaxhumana ngayo nama-LLM. imfundo engahlelwanga kahle Kungaholela ezimpendulweni ezingacacile, ikhodi engalungile, noma ngisho nokubona izinto ezingekho ngokoqobo kodwa ezingamanga. Ngokuphambene nalokho, isixwayiso esihle singaba umehluko phakathi kwethuluzi elingenamsebenzi kanye nesici esibalulekile kuhlelo lwakho lokusebenza.
Ubunjiniyela obusheshayo abugcini nje "ekuceleni izinto ezinhle": buhilela ukuklama, ukuhlola, ukukala kanye nokuthuthukisaLokhu kufaka phakathi ukuqonda lokho imodeli ekwaziyo nengazi, indlela yokuphatha umongo wayo, indlela yokuphoqa imiphumela ehlelekile (isb., i-JSON noma i-HTML), kanye nendlela yokuyihlanganisa namanye amathuluzi afana nalawa yolwaziizinjini zokusesha noma izinhlelo zamafayela.
Imodeli eyisisekelo vs imodeli yemiyalelo: okufanele ukhethe kumaphrojekthi akho
Ngaphambi kokubhala isicelo sakho sokuqala esibalulekile, kuyasiza ukuqonda umehluko phakathi kwe- imodeli eyisisekelo (isisekelo) kanye ne imodeli ilungiswe ngokwemiyalelo (kulungiswe imiyalelo). Lo mehluko uyisihluthulelo sokuthuthukisa izinhlelo zokusebenza ezinokwethenjelwa.
Un Isisekelo se-LLM Uqeqesha kuphela bikezela igama elilandelayoKufana nemodeli enkulu yokuqedela ngokuzenzakalela: kungenzeka ukuthi iqeda imisho, kodwa ayilungiselelwe ukulandela imiyalo noma ukugcina ingxoxo ehambisanayo, futhi ingaziphatha ngendlela exakile noma engalindelekile ngokwemiyalelo.
Un I-LLM yemiyalelo Yakhiwe kusukela kumodeli eyisisekelo futhi icwengisisiwe ukuze Landela imiyalelo ngolimi lwemveloNgaphezu kwalokho, ngokuvamile kudlula esigabeni se-RLHF (ukufunda kokuqinisa ngempendulo yabantu), lapho kufundiswa khona ukuba ngcono ewusizo, ethembekile, futhi engenangoziukujezisa izimpendulo ezingafanele nokuvuza izimpendulo ezinhle.
Ngezinhlelo zokusebenza zangempela, ngaphandle kokuthi unesizathu esithile, cishe uzofuna njalo ukusebenzisa uhlobo lwemodeli "yengxoxo", "yokufundisa" noma "yomsizi"Uma usebenza namamodeli omthombo ovulekile, uzobona ukuhlukahluka okufana nezinguqulo "eziluhlaza" noma "eziyisisekelo" uma kuqhathaniswa nezinguqulo "zengxoxo" noma "ezokufundisa". Ku-bot yokusekela, umsizi wekhodi, noma uhlelo lokuhlaziya umbhalo, cishe njalo khetha inguqulo yemiyalelo.
Ukusetha indawo yakho: kusukela ku-LLM yendawo kuya ku-API
Njengonjiniyela, ungaxhumana ne-LLM ngokusebenzisa I-API evela kumhlinzeki wesithathu (I-OpenAInoma ukusebenzisa i- imodeli yendawo ngamathuluzi anjenge-LM Studio, i-Ollama noma amanye amaseva ahambisana ne-OpenAI API.
Isu eliwusizo kakhulu ukuqala imodeli yendawo kwimodi yeseva ye-HTTP bese usebenzisa I-OpenAI SDK esemthethweni (noma enye ehambisanayo) ngokushintsha nje i-URL eyisisekelo kanye nokhiye we-API. Ngale ndlela, ikhodi yakho ayishintshi kangako uma unquma ukusuka kumodeli yendawo uye kumodeli yefu ekhokhelwayo.
Isibonelo, ungahlanganisa umsebenzi omncane womsizi ku-Python, into efana ne- thola_ukuqedwa othola isaziso bese ubuyisela umbhalo oqediwe. Yilapho unquma khona imodeli ozoyisebenzisa, inani lokushisa (eliphansi lokukhipha okuphindaphindwayo, eliphakeme lokudala okwengeziwe), kanye umlayezo wesistimu lokho kubeka ukuziphatha okuvamile komsizi (isibonelo, ukuthi uhlala ephendula ngesiSpanishi).
Lolu hlobo lokusonga lukuvumela shintsha ngokushesha ngezilungiselelo zakho kusuka ku-Jupyter Notebook noma ku- iskripthi okuvamile, ukuhlola imibono, ukuqhathanisa imiphumela, futhi ngaphezu kwakho konke, ukuguqula lokho okwakudlalwa nge-ChatGPT kube inqubo yokuthuthukiswa ephindaphindwayo.
Izimiso ezimbili eziyisisekelo zobunjiniyela obusheshayo
Ngemuva kwezinhlobonhlobo ezinkulu zamasu ozowabona, cishe konke kungafingqwa kanje: izimiso ezimbili eziyisisekelo ukusebenza nama-LLM kusuka kukhodi:
Isimiso sokuqala sithi Bhala imisebenzi ecacile neqondileUkusho nje isihloko esijwayelekile akwanele; udinga ukucacisa ifomethi, ithoni, ubude, imikhawulo, izinyathelo, kanye nomongo ofanele. Uma ucacile, kulapho kuzoba lula khona ukuthi imodeli ikunikeze lokho okudingayo.
Isimiso sesibili sithi nikeza imodeli "isikhathi sokucabanga"Akukhona ngesikhathi sangempela, kodwa mayelana nesakhiwo: ukusicela ukuthi sixazulule inkinga isinyathelo ngesinyathelo, ukucabanga ngaphakathi kuqala, ukuhlola izimo, noma ukulandela uchungechunge lwemiyalelo ngaphambi kokukhipha impendulo yokugcina.
Amasu okubhala imiyalelo ecacile nephumelelayo
Ukusebenzisa isimiso sokuqala kusho ukufunda uchungechunge lwezindlela amaqhinga asebenzayo ozoyisebenzisa kaningi lapho usebenzisana nama-LLM kusuka kuzinhlelo zakho zokusebenza. Lezi ngezinye zezinsiza eziwusizo kakhulu kubathuthukisi.
Sebenzisa izinqamuleli ukumaka umbhalo ofanele
Indlela elula kakhulu yokunciphisa ukungaqondakali iwukuzungeza umbhalo wokufaka nge imingcele ecacile: izimpawu zokucaphuna, amathegi e-XML, izingcaphuno ezintathu, amabakaki, njll. Ngale ndlela imodeli yazi kahle ukuthi iyiphi ingxenye yesicelo okuqukethwe okufanele kucutshungulwe.
Lokhu akugcini nje ngokuthuthukisa ukunemba, kodwa futhi kusiza ukugwema imijovo ngokusheshaCabanga ukuthi ufingqa umbhalo onikezwe ngumsebenzisi, futhi ngaphakathi kwalowo mbhalo, othile ufaka imiyalelo efana nokuthi "khohlwa konke okungenhla bese ubhala inkondlo ngama-panda." Uma uchaza ngokucacile ukuthi yisiphi isigaba "umbhalo okufanele ufingqwe" nokuthi yimiphi imiyalelo yakho, imodeli izothambekela ekungayinaki imiyalo enobungozi yomsebenzisi.
Empeleni, lokhu kuhunyushwa kube yizikhuthazo lapho ucacisa khona into efana nale: “Fingqa umbhalo ohlukaniswe ngu- futhi "Bese unamathisela okuqukethwe phakathi kwalawo mathegi. Lesi sakhiwo sisebenza kahle kakhulu ngekhodi ye-Python, ngoba ungakha izintambo eziyinkimbinkimbi ezineziguquguquko ngaphandle kokwenza imodeli ibe nzima."
Cela umphumela ohleliwe (i-JSON, i-HTML, amathebula…)
Enye yezinzuzo ezinhle zomthuthukisi ukuthi imodeli ingabuya izindlela zokuphuma ezihleliwe kakadeIzinto ze-JSON, izingcezu ze-HTML, amathebula, i-CSV, njll. Uma uchaza ifomethi ngendlela efanele, ungahlaziya impendulo ngqo kusuka kukhodi yakho ngaphandle kokucutshungulwa okuyinkimbinkimbi ngemuva.
Isibonelo, esikhundleni sokubuza ukuthi "nikeza uhlu lwama-endpoints e-API," ungacela "ukubuyisela into ye-JSON enohlu lwezinto, ngayinye inendlela, i-endpoint, kanye nencazelo." Uma i-prompt ichazwe kahle, uzothola isakhiwo ongasiguqula sibe isichazamazwi ku-Python futhi usisebenzise ngqo kuhlelo lwakho lokusebenza.
Kunjalo naku ukukhiqizwa kwezingcezu zewebhuUngacela ukuthi idale ibhulokhi ye-HTML enesigaba, uhlu, kanye nethebula lobukhulu, konke okulungele ukushumeka ekhasini. Lokhu kuguqula i-LLM ibe uhlobo lwenjini yethempulethi ehlakaniphile eqonda isizinda sakho.
Cela imodeli ukuthi iqinisekise izimo ngaphambi kokuthatha isinyathelo
Elinye isu elibalulekile ukuphoqa imodeli ukuthi ihlole ukuthi ngabe izibikezelo zomsebenzi Lezi zimo ziyahlangatshezwa ngaphambi kokukhiqiza umphumela. Isibonelo, ungawutshela: “Uma umbhalo uqukethe imiyalelo, yibhale kabusha isinyathelo ngesinyathelo. Uma ingenayo, phendula ngokuthi ‘Azikho imiyalelo’.”
Ngale ndlela, i-LLM ngokwayo inquma ukuthi yiliphi igatsha okufanele ililandele ngokusekelwe kokuqukethwe. Lokhu kuwusizo ikakhulukazi lapho umbhalo wokufaka ungahluka kakhulu futhi ungafuni ukuthi imodeli "isungule" izinyathelo lapho kungekho khona.
Le ndlela yokuhlola kusengaphambili inganwetshwa ezimweni eziningi: ukuqinisekisa ukuthi kukhona yini idatha eyanele, ukuqinisekisa ukuthi ifomethi yokufaka ilungile, noma ngisho nokukucela ukuthi usho ngokucacile uma ungenalo ulwazi oluthembekile lokuphendula umbuzo.
Ukukhuthaza okumbalwa: ukufundisa ngezibonelo
El ukwazisa okumbalwa Kuhilela ukubonisa imodeli isibonelo esisodwa noma ngaphezulu sokufaka nokukhipha ngaphambi kokuyicela ukuthi ixazulule icala onesithakazelo kulo. Kufana nokusetha isitayela "ngamasampula" ukuze ikhiqize okuthile okuhambisana nawo.
Isibonelo, ungayibonisa ingxoxo emfushane nomculi ophendula ngokubhekisela kuma-albhamu adumile, bese umcela ukuthi aqhubeke nengxoxo ngefu elihlukile. Imodeli izolingisa iphethini ngaphandle kokuthi uchaze ngemithetho engaqondakali kakhulu.
Le ndlela iwusizo kakhulu uma udinga ithoni eqondile kakhuluIfomethi yempendulo engaguquki noma ukuguqulwa kwedatha okungambozwanga kahle yimiyalelo elula. Esikhundleni sokuchaza, ufundisa, njengoba nje ubungenza nozakwenu osemncane.
Nikeza "isikhathi sokucabanga": yenza isibonelo sibe yisizathu
Isimiso sesibili sigxile endleleni yokufeza imodeli UngasheshiAma-LLM avame ukuqeda impendulo ngokushesha ngokulandela amaphethini, kodwa emisebenzini eyinkimbinkimbi (ikakhulukazi eyezibalo, enengqondo, noma enezinyathelo eziningi) kungcono ukuwaphoqa ukuthi hlukanisa inkinga.
Indlela eqondile yokwenza lokhu ukucela ngokusobala eyodwa uchungechunge lokucabanga (“uchungechunge lwemicabango”), okubonisa ukuthi kufanele kuqala ichaze ukuthi ifika kanjani emphumeleni bese inika impendulo yokugcina. Okunye ukuhlela isisho ngezinyathelo ezinezinombolo: “1) Qalisa kabusha, 2) Humusha, 3) Khipha amagama, 4) Buyisela i-JSON…”.
Kusebenza kahle kakhulu ukumtshela lokho Xazulula lo msebenzi ngokwakho ngaphambi kokuhlola ikhambi lomfundi.Okokuqala, yenza izibalo zayo, bese iziqhathanisa nesixazululo esiphakanyisiwe bese inquma ukuthi zilungile noma cha. Le ndlela inciphisa kakhulu amathuba okuthi imodeli izoqinisekisa izixazululo ezingalungile njengezilungile ngenxa nje yomkhuba.
Amacala okusetshenziswa abalulekile konjiniyela: kusukela ezifinyezweni kuya ku-NLP ethuthukisiwe
Uma usuziqondile izimiso, isinyathelo esilandelayo ukubona izimo zokusetshenziswa eziqondile lapho i-LLM isebenza njengenye imojuli yesistimu yakho. Eziningi zalezi zithatha indawo noma zihambisana namamodeli e-NLP akudala.
Fingqa umbhalo ngendlela elawulwayo
Enye yezindlela ezisetshenziswa ngqo kakhulu ukucela imodeli ukuthi Fingqa izibuyekezo, izindaba, ama-imeyili, noma imibhalo, isibonelo for Fingqa noma ubuze i-ebook ene-AIInto ethakazelisayo ukuthi ungakwazi ukulawula ubude kanye nokugxila kwesifinyezo: “amagama angu-30 aphezulu”, “imisho engu-3 ephezulu”, “gxila isifinyezo ekusetshenzisweni kwamandla”, njll.
Ungashintsha futhi phakathi kokuthi “fingqa” nokuthi “khipha”: esikhundleni sokucela umbhalo ofingqiwe, ungawucela ukuthi ukhiphe idatha ethile kuphela (intengo, ukusebenza, izikhalazo eziphindaphindayo, njll.). Lolu shintsho olucashile kulesi sicelo luguqula isifinyezo esijwayelekile sibe umtholi wolwazi oluwusizo lwebhizinisi lakho.
Ukuhlaziywa kwemizwa kanye nokukhishwa kwento
Ama-LLM ayakwazi ukwenza ukuhlaziywa kwemizwelo (okuhle, okubi, okungathathi hlangothi) kanye nokutholakala kwemizwelo (intukuthelo, ukukhungatheka, injabulo…) ngqo kusuka embhalweni. Lokhu kukuvumela ukuthi uqaphe ukubuyekezwa, amathikithi okusekela, noma amazwana ezinkundleni zokuxhumana ngaphandle kokuqeqesha imodeli ethile yokuhlukanisa.
Ngokufanayo, ungayicela ukuthi ichaze izinto ezibalulekile (umkhiqizo, uhlobo, umuntu, indawo) bese ubuyisela umphumela entweni elula ye-JSON enezihluthulelo ezifana ne-Item kanye nohlobo. Le ndlela iwusizo ekwakheni amadeshibhodi angaphakathi, ukubeka phambili izikhalazo, noma ukucebisa idatha yamakhasimende ngaphandle kokusetha ipayipi lendabuko le-NLP.
Ukutholwa kwesihloko kanye nokuhlukaniswa ngezigaba
Omunye umsebenzi owusizo ukucela imodeli ukuthi ithole izihloko eziyinhloko embhalweni bese uwaveza njengamathegi amafushane ahlukaniswe ngamakhoma. Ungavumela imodeli ukuthi isungule izihloko noma uyikhawulele ohlwini oluchazwe kusengaphambili ("usekelo lobuchwepheshe, ukukhokhisa, umkhiqizo, izinkinga zokuthumela ...").
Lokhu kusenza sikwazi ukwenza ukuhlukaniswa kwamathikithi, ama-imeyili noma izindaba zomsebenzisi ngaphandle kokuqeqesha abahleli abaqondisiwe, futhi ngesikhathi esifanayo besebenzisa umongo wencazelo oqoshwa yi-LLM enkulu.
Ukuhumusha, ukuhlaziya kanye nokuguqulwa kombhalo
Amamodeli aphezulu afunde, njengomphumela ongemuhle wokuqeqeshwa kwawo okukhulu, ukuhumusha phakathi kwezilimi eziningiBalungisa amaphutha ohlelo lolimi kanye nopelo futhi babhale kabusha imibhalo ngemisindo ehlukene. Nakuba babengaqeqeshwanga njengabahumushi abangochwepheshe, basebenza kahle ngokumangalisayo.
Ungacela ukuhumusha okuqondile ("ukuhumusha lo mbhalo kusuka esiNgisini kuya eSpanishi"), ukutholwa kolimi ("ngitshele ukuthi lo musho ungoluphi ulimi") noma ukulungiswa ("lungisa umusho olandelayo bese ungitshela kuphela inguqulo elungisiwe; uma ungaboni amaphutha, phendula ngokuthi 'Akukho phutha'").
Kumthuthukisi, lokhu kuvula ithuba lokuthi Amathuluzi okubuyekeza okuqukethwe, ukwenziwa kombhalo kube ngokwejwayelekile ngaphambi komzila we-ML noma okuhlangenwe nakho kwezilimi eziningi ngaphandle kohlelo lokuhumusha oluzinikele. Kodwa-ke, kubalulekile ukukhumbula ukuthi imodeli nayo ingaba yiphutha, ikakhulukazi ngemibhalo yobuchwepheshe obukhulu noma izimo ezingacacile.
Ukwakha ama-chatbot anenkumbulo: izindima kanye nomongo wengxoxo
Uma usuka ezingcingweni ze-API ngazinye uye ku- ama-chatbots ezingxoxoKuvela inkinga enkulu: imodeli ezenzakalelayo, akakhumbuli imiyalezo yangaphambiliniIsicelo ngasinye sicutshungulwa ngokuzimela.
Ukuze ulingise inkumbulo udinga Gcina umlando wemilayezo kuhlelo lwakho lokusebenza bese uyithumela kukholi ngayinye, usebenzisa isakhiwo sendima esijwayelekile: umlayezo wesistimu ochaza ukuthi ungubani umsizi, imiyalezo yomsebenzisi equkethe lokho umuntu akubuzayo, kanye nemiyalezo yomsizi enezimpendulo zangaphambilini zemodeli.
Isibonelo, uma ekuqaleni umsebenzisi esho igama lakhe bese kwesibili ebuza ukuthi "ngingubani igama lami?", uzothola impendulo efanele kuphela uma ufaka umlando lapho lolo lwazi lushiwo khona esicelweni samanje. Uma uthumela umlayezo wokugcina kuphela, imodeli ngeke ibe nendlela yokwazi.
Le phethini ikuvumela ukuthi udale kusuka ku- ama-robot okusekela ezentengiselwano ze-inthanethi (abakhumbula i-oda elichazwe yikhasimende) kubasizi bangaphakathi bamaqembu okuthuthukisa noma ezezimali, inqobo nje uma ulawula ukuthi umlando awukhuli kakhulu kangangokuthi ubangele izindleko noma izikhathi zokuphendula.
Isibonelo esisebenzayo: i-bot yoku-oda i-pizza ene-LLM
Isibonelo esijwayelekile sokuqonda ukuthi ungakufaka kanjani konke lokhu kukhodi ukwakha i- uku-oda i-bot ye-pizzeriaEmyalezweni wesistimu uchaza ukuthi i-bot ingubani, isebenzisa yiphi ithoni, yimiphi imikhiqizo ekumenyu kanye namanani ayo, nokuthi yiziphi izinyathelo okufanele izilandele (bingelela, thatha i-oda, buza ukuthi ingabe ingeye-takeaway noma i-lack, cela ikheli uma kudingeka, njll.).
Bese, ku-loop yakho eyinhloko, ufaka yonke imiyalezo eshintshiwe ohlwini. Isikhathi ngasinye lapho umsebenzisi esho okuthile, ufaka umlayezo onendima yomsebenzisi; ubiza umsebenzi wakho we-get_completion_from_messages ngalolo hlu oluphelele; ufaka impendulo yemodeli enendima yomsizi; bese ubonisa umbhalo obuyiselwe.
Ngemigqa embalwa yekhodi ungathola imodeli Phatha ingxoxo, uqinisekise i-oda, bese ubala isamba.Ngaphandle kokufaka ikhodi eqinile, ukugeleza kwengxoxo okuqinile. Okuwukuphela kwezinto ozihlelile ngokucacile yimiyalelo ephezulu kumyalezo wesistimu kanye ne-loop logic yokugcina umlando.
I-RAG kanye nokusetshenziswa komongo wangaphandle ukuze kutholakale izimpendulo ezibuyekeziwe
Nakuba ama-LLM eqeqeshwa ngombhalo omningi, ulwazi lwawo Akuyona into engenamkhawulo futhi ayihlali isesikhathiniUma ufuna baphendule ngokusekelwe kumadokhumenti angaphakathi, izisekelo zolwazi, amakhathalogi emikhiqizo, noma amanothi ayimfihlo, udinga ukuhlinzeka lowo mongo wena ngokwakho.
Yilapho-ke Isizukulwane Esithuthukisiwe Sokubuyisela (RAG)Lena iphethini lapho uhlanganisa khona injini yokusesha ye-semantic (esekelwe ekufakweni) nemodeli yokukhiqiza. Ukugeleza okuvamile yilokhu: uguqula amadokhumenti akho abe ama-vector, ugcine lawo ma-vector endaweni yokugcina (i-Pinecone, i-Chroma, i-vector databases, njll.), futhi lapho umsebenzisi ebuza, usesha izingcezu ezifanele kakhulu bese uzidlulisela ku-LLM ngaphakathi kwesicelo njengomongo.
Ngokombono wobunjiniyela obusheshayo, lokhu kusho ukuklama imiyalelo efana nalokhu: “Phendula umbuzo usebenzisa ulwazi kuphela kumongo olandelayo. Uma ungakwazi ukuthola impendulo lapho, yithi awazi.” Lokhu kunciphisa iziphazamiso futhi kukusiza ukuthi uthole imiphumela engcono. izimpendulo ezenzelwe isizinda sakhongaphandle kokuqeqesha kabusha imodeli.
Qaphela imibono engekho kanye nokulinganiselwa komodeli
Esinye sezixwayiso ezibaluleke kakhulu lapho usebenza nama-LLM ukuthi ulwazi lungakhiwa ngendlela ekholisayo kakhulu. Uma umbuza imininingwane ngomkhiqizo oqanjiwe onegama elingokoqobo, imodeli cishe izokhipha incazelo ephelele emlonyeni wakhe, okuhlanganisa izakhiwo, ukusetshenziswa, kanye nezinzuzo.
Lokhu akubangelwa yinhloso embi, kodwa kungenxa yokuthi imodeli ifunde amaphethini ombhalo futhi igcwalisa izikhala ngalokho "okuzwakala sengathi kungenzeka." Yingakho kubalulekile ezindaweni ezibucayi (ukunakekelwa kwempilo, ezezimali, ezomthetho, izeluleko zobuchwepheshe ezibucayi). ungathembi ngokungaboni yezimpendulo bese usungula izendlalelo ezengeziwe zokuqinisekisa.
Ngokombono womyalo, unganciphisa ingxenye yenkinga ngokucela imodeli ukuthi ibone ukuthi nini Ayinalo ulwazi olwaneleImiyalelo efana nokuthi “uma ungaqiniseki, yisho ngokucacile” iyasiza, futhi ukuyihlanganisa ne-RAG ukuze inikeze umongo onokwethenjelwa kuthuthukisa kakhulu ukuqina kwesixazululo.
Ukuthuthukiswa okusheshayo okuphindaphindiwe: ukuhlola, ukulinganisa, kanye nokucwenga
Akukho sicelo esingathi sína esike saphuma kahle okokuqala. Ukusebenza nama-LLM kuhilela ukwamukela isimo sengqondo sokuthi ukuthuthukiswa okuphindaphindayoUkhipha inguqulo yokuqala, ubone ukuthi yini ehlulekayo, ulungise imiyalelo, uvivinye futhi, bese uphinda umjikelezo kuze kube yilapho ukuziphatha kuzinzile ngokufanele.
Indlela enhle ukuqala ngomqondo ojwayelekile (“Ngifuna incazelo yomkhiqizo wewebhusayithi yefenisha esekelwe kuleli shidi ledatha”) bese ufaka kancane kancane imikhawulo: umkhawulo wamagama, ithoni yobuchwepheshe noma yezentengiselwano, ukufakwa kwama-ID omkhiqizo, ukwenziwa kwamathebula e-HTML, njll. Ukuphindaphinda ngakunye kukufundisa okuthile ngendlela imodeli echaza ngayo imiyalelo yakho.
Ezimweni zokusetshenziswa eziyinkimbinkimbi, kungaba wusizo ngisho izivivinyo zokwenza ngokuzenzakalelayoLungisa isethi yezibonelo zokufaka, sebenzisa isixwayiso esifanayo kuzo zonke, bese uhlaziya imiphumela ukuze uthole amaphethini amaphutha noma ukungahambisani, njengoba nje ubungenza ngezivivinyo zamayunithi noma zokuhlanganisa.
Empeleni, ukuba yingcweti kwezobunjiniyela obusheshayo kusho lokhu ngqo: ukwazi ukufunda izimpendulo zemodeli, ukuhlonza ukuthi iyiphi ingxenye yesicelo engacacile bese uyiphinda uyibeke ngokunemba komuntu ochithe iminyaka echaza izidingo kwabanye onjiniyela.
Uma zihlanganiswa, zonke lezi zindlela zenza i-LLM ibe ithuluzi eliqinile ngaphakathi kwesitaki sakho: ungalisebenzisa ukuze khiqiza ikhodiUkubukeza izixazululo zabafundi, ukufingqa amadokhumenti, ukuhlela amathikithi ngezigaba, ukuphendula imibuzo mayelana nedatha yakho, noma ukwakha ama-chatbot akhethekile. Uma uqonda kangcono amandla ayo kanye nokulinganiselwa kwayo, kulapho uzokwazi kangcono ukuthi uzoyethemba nini nokuthi ungazibhala kanjani izimpendulo ezikhulisa amakhono ayo ngaphandle kokulahlekelwa ukulawula kobuchwepheshe kohlelo lwakho lokusebenza.
Umbhali oshisekayo ngomhlaba wamabhayithi nobuchwepheshe ngokujwayelekile. Ngiyathanda ukwabelana ngolwazi lwami ngokubhala, futhi yilokho engizokwenza kule bhulogi, ngikubonise zonke izinto ezithakazelisayo kakhulu ngamagajethi, isofthiwe, ihadiwe, izitayela zobuchwepheshe, nokuningi. Inhloso yami ukukusiza ukuthi uzulazule emhlabeni wedijithali ngendlela elula nejabulisayo.