Kedis ku xidhan hagaha · Dhexdhexaad Heerka
Kediska Hababka Qaababka Goynta Malaha
Sahaminta soo jeedinta qaab-qabyo ah, xaqiijinta bartilmaameedka, muunad diidmada, ixtimaalka aqbalaadda, calaamadaha gunnada, iyo xawaaraha ku-tiirsanaanta shaqada.
Su'aal 1 ee 8
Waa maxay doorka aasaasiga ah ee qaabka 'qabyo' ee dejinta malo-awaalka ah?
Horudhac su'aal kasta8 su'aalo
Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.
- Waa maxay doorka aasaasiga ah ee qaabka 'qabyo' ee dejinta malo-awaalka ah?
- Si loo cadaadiyo qaabka weyn si joogto ah oo xaddidan
- Si degdega loogu turjumo luqad kale
- In si degdeg ah loo soo jeediyo dhowr calaamadood oo musharrax ah oo loogu talagalay qaabka weyn si loo xaqiijiyo
- Si loo kaydiyo sheekadii hore ee soo celinta
- Why can verifying a drafted token block accelerate target-model generation in a suitable workload?
- Verification has no compute cost at any block size
- A verification pass can process several positions together and amortize target work across accepted tokens
- The draft model is guaranteed more accurate than the target
- The target model is skipped for every accepted token
- Maxaa ku dhacaya calaamadihii la diyaariyay kadib calaamadii ugu horeysay ee qaabka bartilmaameedku diido?
- Wax kasta ka dib is-maan-dhaafka ugu horreeya waa la tuuraa
- Dhammaantood waa la aqbalay si kastaba
- Waxaa loo diraa nooc saddexaad
- Waa la kaydiyay oo dib ayaa loo istcimaali jiray leexashada xigta
- What correctness property does the standard exact speculative-sampling rejection procedure preserve under its assumptions?
- An identical random sequence for every possible random seed
- Guaranteed truth of every generated statement
- The draft model's distribution regardless of the target
- The target model's configured sampling distribution
- Which mechanism distinguishes EAGLE's drafting approach from Medusa's additional decoding heads?
- EAGLE performs only word-count-based lexical retrieval
- EAGLE drafts autoregressively at the target model's feature level
- EAGLE removes target verification from every algorithm
- EAGLE and Medusa are the same architecture with different names
- Why should a speculative-decoding benchmark report the draft-target pair and acceptance rate?
- Every model pair has the same guaranteed speedup
- Acceptance rate measures whether generated facts are true
- Speedup depends on drafting and verification costs and how many proposed tokens are accepted
- The target model's hardware and context length cannot affect performance
- In exact speculative sampling, a proposed token has q equal to 0.2 and p equal to 0.1. What is its acceptance probability?
- 0.1, because only p is used
- 0.2, because only q is used
- 1.0, because every proposed token is accepted
- 0.5, from min(1, p/q)
- What can the standard speculative-sampling algorithm emit when every token in a drafted block is accepted?
- The accepted block plus an additional token sampled from the target
- Only the last drafted token, discarding the accepted prefix
- An arbitrary extra draft token without target sampling
- No output until the draft model is retrained