Kediska Xisaabinta Model

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Quantizing a model mainly reduces what?
   • Saxnimada tirada ee loo isticmaalo in lagu kaydiyo miisaanka iyo hawlgelinta
   • Tirada lakabyada shabakada
   • Xogta tababarka qaabka ayaa lagu dhisay
   • Luuqadda uu model-ku fahmi karo
2. Ignoring scale metadata and other runtime tensors, what is the weight-payload ratio from sixteen bits to four bits per weight?
   • The payload is unchanged
   • It is one hundredth of the original payload
   • The four-bit payload is one quarter of the sixteen-bit payload
   • The payload becomes four times larger
3. Waa maxay hoos-u-dhaca ugu weyn ee tirada-yar-yar ee gardarrada leh?
   • Qaabka ayaa iloobaya luqadiisa tababarka
   • Luminta suurtagalka ah ee saxnaanta marka qiyamka lagu tuujiyo baaldiyo yar
   • Waxa ay ku socon kartaa oo kaliya supercomputer
   • Waxay si joogto ah u tirtirtaa lakabyada
4. Sidee buu tabobarka xog-warranka uga duwan yahay tirooyinka tababarka ka dib?
   • Wax xog ah uma baahna haba yaraatee
   • Waxay kaliya ku shaqeysaa sawirada
   • Waxay kordhisaa tirada xoogaa waqti ka dib
   • Waxay u ekaysiisaa isku darka inta lagu jiro tababarka si moodalku u barto inuu u dulqaato saxnaanta hoose
5. Farsamokee adeegsata 4-bit quantization si ay u hagaajiso moodooyinka waaweyn ee la awoodi karo hal GPU?
   • Ka saarida
   • Dufcaddii caadiga ahayd
   • QLoRA
   • Calaamadaynta
6. Waa maxay sababta ay kanaalka-kasta ama koox-koox kasta u caawinayso moodooyinka la qiyaasey?
   • Waxay u qoondaysaa arrimo miisaan oo gaar ah jeexjeexyada shaxanka miisaanka si loo ilaaliyo saxnaanta
   • Waxay meesha ka saartaa baahida miisaan kasta
   • Waxay ka dhigaysaa qaabka mid weyn
   • Waxa ay qoraalka u beddeshaa maqal
7. A four-bit model’s raw weights fit in available VRAM, but serving fails out of memory. What could explain this?
   • Every four-bit weight expands permanently to a gigabyte
   • Quantization guarantees no runtime allocations
   • Only the model’s filename consumes the remaining memory
   • Caches, scales, unquantized tensors, or workspace need additional memory
8. A team quantizes to INT8 but sees no inference speedup. What should it check?
   • Whether the training data are alphabetized
   • Whether the workload uses efficient supported kernels on its hardware
   • Whether lower bit width always guarantees faster execution
   • Whether the model must have changed languages