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Fine-Tuning vs RAG vs Prompting
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QLoRA iyo 4-Bit Fine-Tuning
QLoRA waa farsamo kuu ogolaanaysa inaad si fiican u habayso moodel luuqadeed oo baaxad leh hal macaamiil GPU ah adiga oo ku kaydinaya moodka barafsan 4 bits oo keliya miisaankiiba.
Dhageyso hagahanAI-waa laga sheekeeyay · ~2 min
Boggaan2 daqiiqo akhri
Dulmar
Waxay ka dhigtay habaynta moodooyinka 65B-parameter ee suurtogalka ah qalabka kuwaas oo markii hore xamili kara oo keliya moodooyinka qayb ka mid ah cabbirkaas.
quusid qoto dheer
Caadi ahaan, hagaajinta qaab weyn waxay ka dhigan tahay in culeys kasta lagu soo raro 16-bit oo sax ah oo la cusboonaysiiyo dhammaantood, taas oo u baahan xusuus aad u weyn. QLoRA waxay isku daraysaa laba fikradood. Marka hore, waxay qaboojisaa moodeelkii hore loo tababbaray oo waxay ku qiyaastaa 4 bits, iyada oo hoos u dhigaysa xusuusta qiyaastii afar laab. Midda labaad, waxay isticmaashaa LoRA: halkii ay ka cusboonaysiin lahayd matrijyada miisaanka aadka u weyn, waxay durisaa qalab-adabatareedyo yar-yar oo tababaran oo hooseeya, markaa dhawr milyan oo cabbir ayaa la cusboonaysiiyaa. Saldhigga 4-bit wuxuu ahaanayaa mid go'an halka gradients-ku ay ku qulqulayaan oo keliya adapters-yada yaryar. Waxaa soo bandhigay 2023 Dettmers iyo asxaabtiisa, QLoRA waxay muujisay in hagaajinta qaabka 65B ee hal 48GB GPU uu la mid noqon karo tayada 16-bit oo dhamaystiran.
Dhaqangelinta Adduunka-dhabta ah
Bilawga ayaa si fiican u laxan mooda 70B Llama hal 48GB GPU si uu u dhiso kaaliyaha taageerada macmiilka ee codkiisa sumadda ah iyada oo aan la kiraysanin koox server ah.
Cilmi-baare leh hal macaamiil RTX 4090 wuxuu ku habeeyaa moodal furan xog-ururinta su'aalaha-ka-jawaabista caafimaad ee ugu fiican habeen.
Horumariyahu waxa uu abuuraa daraasiin yar yar oo la isku bedeli karo LoRA adabtarada hawlo kala duwan, dhamaantood waxa ay wadaagaan hal nooc oo 4-bit ah oo ku raran xusuusta.
Hiwaayad-yaqaanka ayaa si fiican u laxanaya tusaalaha diiwaanka sheekadooda gaarka ah si ay ugu ekaadaan qaab qoraal oo gaar ah iyaga oo isticmaalaya qalab-class-Colab bilaash ah.
Mustaqbalka QLoRA iyo 4-Bit Fine-Tuning
4-bit ganaax-ku-habboon waxa ay noqotay hab-dhaqan caadi ah, cilmi-baadhistuna hadda waxa ay u riixdaa xattaa saxnaanta hoose, oo ay ku jiraan 2-bit iyo 1-bit (ternary). Nidaamyada cusub ee xisaabinta sida AWQ, GPTQ, iyo HQQ ayaa sii sifeynaya saxnaanta, halka farsamooyinka ay ka midka yihiin QA-LoRA ujeedadoodu tahay in la qiyaaso qaabka xitaa ka dib marka la isku daro adapters. Sida moodooyinka miisaanka-furan ay koraan, filo qalabaynta u oggolaanaysa hiwaayadaha 70B-plus moodooyinka hal ciyaar GPU inay noqdaan kuwo joogto ah, dimuqraaddiynaya habaynta.
Ku dhaqangelinta
Maxay muhiim u tahay
- Xawaaraha iyo miisaanka. Socodka shaqada luqaddu si dhakhso leh ayay u socon kartaa iyada oo aan la hurayn joogteynta.
- Helitaanka iyo gaarsiinta. Waxay balaadhisaa gelitaanka luqadaha iyo qaababka isgaarsiinta.
- Go'aamo cad. Kooxuhu waxay waqti badan ku qaadan karaan xukunka halka otomaatiggu uu qabanayo ku celcelinta.
Iska ilaali
- Xaqiiqooyinka dhalanteed waxay si deggan u geli karaan warbixinnada, taageerada socodka, ama natiijooyinka cilmi-baarista.
- Dareenka degdega ahi wuxuu abuuri karaa natiijooyin aan iswaafaqayn codsiyada la midka ah.
- Xogta qoraalka xasaasiga ah ayaa laga yaabaa in la kashifo haddii kontaroolada gelitaanka ay daciif yihiin.
Tallaabooyinka xiga
- Qeex qaabka wax soo saarka, codka, iyo heerarka tayada ka hor inta aan la baahin.
- Jawaabaha salka ku haya ilo lagu kalsoon yahay mar kasta oo saxnidu ay muhiim tahay.
- Hayso isbaarada dib u eegista bini aadamka ee wax soo saarka sare.
- Lasoco qaababka guuldarada oo dib u leyli dardargelinta ama socodka shaqada si joogto ah.
Sii wad Sahaminta
Warqad bilaash ah
Hel warbixinta maalinlaha ah ee AI
Saddex sheeko oo la xaqiijiyay oo AI ah maalin kasta oo shaqo ah, oo lagu qoray Ingiriis fudud. Bilaash had iyo jeer, aan xayaysiis lahayn.
Hal iimayl maalin kasta oo shaqo ah. Ka bax hal gujin. Marna ma iibinno ama ma wadaagno ciwaankaaga.
Is tijaabi
Take the QLoRA and 4-Bit Fine-Tuning quiz
Fikrad degdeg ah oo ku saabsan jawaab kasta, iyo shahaado la wadaajin karo oo leh aqoonsi la xaqiijin karo markaad ka gudubto koorso.
Taageer waxbarashada AI bilaashka ah. AI Understanding waa 501(c)(3) aan faa'iido doon ahayn — xayaysiis la'aan, albaab lacag ah ma jiro, had iyo jeer. Samee deeq
Su'aalaha soo noqnoqda
Waa maxay QLoRA iyo 4-Bit Fine-Tuning?
QLoRA waa farsamo kuu ogolaanaysa inaad si fiican u habayso moodel luuqadeed oo baaxad leh hal macaamiil GPU ah adiga oo ku kaydinaya moodka barafsan 4 bits oo keliya miisaankiiba. Waxay ka dhigtay habaynta moodooyinka 65B-parameter-ka ee suurtogalka ah qalabka kuwaas oo markii hore xamili kara oo keliya moodooyinka qayb ka mid ah cabbirkaas.
Waa maxay fikradda kaydinta xusuusta xudunta ah ee ka dambeysa qaybta '4-bit' ee QLoRA?
QLoRA waxay ku kaydisaa miisaanka la barafeeyay ee la barafeeyay 4 bits qiima kasta, iyada oo jaraysa xusuusta qiyaas ahaan afar laab marka loo eego 16-bit.
Inta lagu jiro hagaajinta hagaajinta QLoRA, cabbirkee ayaa dhab ahaantii lagu cusboonaysiiyaa farcanka gradient?
Qaabka salka ayaa la qaboojiyey; Kaliya shaybaarada adabtarada ee darajada hoose ee la duray ayaa helaya cusboonaysiinta gradient, taas oo ah qayb yar oo cabirro ah.
Waa maxay NF4 marka loo eego macnaha guud ee QLoRA?
NF4 (NormalFloat 4-bit) waa nooc xog ah oo loogu talagalay agagaarka qalooca gambaleelka ee culeysyada shabakada neerfaha si ay sax ahaan uga wanaagsan tahay int4 cad.
Dhibaato noocee ah ayaa 'boogaysa-boogaysa' ka qabta ciwaanka QLoRA?
Paged optimizers use NVIDIA unified memory to page optimizer states between GPU and CPU memory as needed; the QLoRA paper says this helps manage memory spikes and reduce out-of-memory risk during long-sequence fine-tuning.
Goorma ayaa miisaanka 4-bit dib loogu noqdaa saxnaanta sare inta lagu jiro tababarka?
During a matrix multiplication, quantized weights are dequantized on the fly to a higher-precision compute dtype (for example, BF16 or FP16 in QLoRA configurations); the temporary higher-precision values are not stored as a full base-model copy.
Sii wad waxbarashada
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