Xalaat garabu xalaat

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

1. Lan moo wuutale Garab-ci-Xalaat ak chaine-ci-xalaat yuy ñaax nit ñi?
   • Dafay banneexu yooni xalaat yu bari ci barabu benn seen ligneer
   • Dina dindi bépp jéego buy xalaat
   • Du dox ludul ci dugal nataal
   • Jëfandikuwul benn xeetu làkk
2. Ci Garab-ci-Xalaat, lan mooy benn node?
   • Tontu bu mujj bu mat sëkk
   • ab pexe bu xaaj wala 'xalaat' bu digg
   • Laaj jëfandikukat
   • Poids buñ tàggat
3. Ban cër la evaluateur réew mi di def ci garabu xalaat yi?
   • Dafay bind tontu bu mujj bi jàkkarloo ak jëfandikukat bi
   • Dafay efaase mémoire model bi
   • Dafay wane ni pexe yu xaaj yi di am njariñ, mën nañu dagg car yu néew doole yi
   • Dafay tekki ci diggante làkk yi
4. Ci Game of 24 benchmark, ToT dafa raw bu baax seen xalaat ci ban tëb?
   • Lu ko dalee ci 90% ba 95%
   • Amul benn yokkute
   • Lu ko dalee ci 50% ba 51%
   • Lu ko dalee ci lu tollu ci 4% dem ba ci lu tollu ci 74%
5. Ban pexe seetlu lañu gëna jëfandikoo ngir seet garabu xalaat bi?
   • Seetug yaatuwaayu njëkk, xóotaayu njëkk, wala seetlu limyéer
   • Xalaat rek
   • Tànneef ci alfabet
   • Wàcci degrade ci kaw pixel yi
6. Lan mooy njëg bi gëna mag ci jëfandikoo Garab-ci-Xalaat?
   • Dafay wàññi njub ngir sakkanal jotu liggéey
   • Dafay laaj xayma yu gëna bari ngir am gëna dëggu
   • Soxlawul woote model yu weesu benn
   • Du dox ludul ci net bi
7. At one Tree-of-Thoughts node, what does the thought generator typically produce?
   • A final answer only, with no intermediate states
   • A new model checkpoint
   • Several candidate next thoughts that could extend the partial solution
   • A set of training labels for the prompt
8. What decision does the ToT search procedure make after candidate states are generated and scored?
   • Which tokenizer the model should use
   • Whether to change the model’s weights
   • How to label the original training corpus
   • Which branches to expand and which to prune or stop exploring