Speculative iṣapẹẹrẹ Idanwo

Awọn idahun ati awọn alaye han bi o ṣe n mu ibeere naa.

1. Kini ero pataki ti o wa lẹhin iṣapẹẹrẹ arosọ?
   • Lo awoṣe iyaworan kekere kan lati daba ọpọlọpọ awọn ami-ami ti awoṣe nla kan jẹrisi ni afiwe
   • Kọ ẹkọ awoṣe nla kan lati fo awọn fẹlẹfẹlẹ ni agbara
   • Kaṣe gbogbo gbolohun ti o ṣeeṣe ni ilosiwaju
   • Rọpo iṣapẹẹrẹ pẹlu iyipada ojukokoro lati fi akoko pamọ
2. Kini idi ti iṣayẹwo akiyesi ko dinku didara iṣẹjade?
   • Nitori awọn osere awoṣe jẹ nigbagbogbo ti o tọ
   • Nitoripe ofin ijẹrisi jẹ ki pinpin ipari jẹ aami kanna si iṣapẹẹrẹ ibi-afẹde mimọ
   • Nitoripe o ṣiṣẹ nikan lori awọn kukuru kukuru
   • Nitoripe o ṣe iwọn awọn abajade awọn awoṣe meji
3. In exact speculative sampling, what happens when a drafted token is rejected?
   • It outputs the rejected draft token unchanged
   • It discards the entire conversation and restarts
   • The algorithm samples from a corrected residual distribution at that position
   • It permanently changes the target model
4. Under exact speculative sampling, what is guaranteed about the output distribution?
   • It is always deterministic
   • It matches the draft model’s distribution instead
   • It is more diverse than every target-model output
   • It matches the target model’s sampling distribution
5. What information does the target verification pass provide in exact speculative sampling?
   • Target probabilities for proposed positions, used for acceptance tests and residual resampling
   • A guarantee that no target-model computation is needed
   • Only the draft model’s next-token distribution
   • A corrected token sequence without any sampling
6. Which description correctly distinguishes two self-speculative approaches?
   • Both use only an unrelated small draft model
   • Medusa adds prediction heads, while EAGLE uses feature-space proposals
   • Medusa is a tokenizer and EAGLE is a reward model
   • Both remove the target model from decoding
7. The draft assigns probability 0.8 to a token and the target assigns 0.4. What is the speculative acceptance probability?
   • 0.2
   • 0.4
   • 0.5
   • 1.0
8. What most limits speculative sampling’s realized speedup?
   • The color of the model’s interface
   • The target model’s name length
   • Whether the prompt contains punctuation
   • The draft-model cost and how much proposed work the target accepts