Idanwo Iyipada Speculative

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

1. Bawo ni iyipada arosọ ṣe iyara iran lati awoṣe nla kan?
   • Awoṣe iyaworan kekere ṣe amoro ọpọlọpọ awọn ami ti awoṣe nla naa jẹri ni afiwe
   • Compressing awoṣe si idaji iwọn rẹ patapata
   • Yiyọ ilana akiyesi
   • Ikẹkọ awoṣe lori data diẹ sii
2. For a large model at low batch size, why can one-token autoregressive decoding be slow?
   • Each token requires internet access
   • Repeated reads of large model weights can make decoding memory-bandwidth bound
   • The model permanently stores a full copy of every possible output
   • The tokenizer performs the model’s matrix multiplications
3. In greedy speculative decoding, what happens at the first token where draft and target predictions disagree?
   • The whole conversation is thrown away and restarted from scratch
   • Awoṣe apẹrẹ ti wa ni atunṣe lẹsẹkẹsẹ
   • The matching prefix is kept, the target token is used at the mismatch, and later draft tokens are discarded
   • Didara ti o wu jade patapata
4. Under exact speculative sampling, how does the output distribution compare with sampling from the target model alone?
   • It is always lower quality but faster
   • It is identical only when the draft model is larger
   • It becomes deterministic regardless of target sampling
   • It is identical in distribution
5. Kini pupọ julọ ṣe ipinnu iyara iyara lati iyipada asọye?
   • Oṣuwọn gbigba ti awọn amoro awoṣe osere
   • Awọn awọ ti GPU
   • Awọn ipari ti awọn awoṣe ká orukọ
   • Akoko ti ọjọ
6. Kini Medusa ati EAGLE ni ni wọpọ bi awọn isunmọ?
   • Wọn nilo ohun elo kuatomu
   • Wọn ṣe imukuro iwulo fun awoṣe iyasilẹ imurasilẹ lọtọ
   • Wọn pa awoṣe afojusun naa
   • Wọn nikan ṣiṣẹ lori awọn aworan
7. What should a serving team measure before claiming speculative decoding will speed up its workload?
   • Only the target model’s parameter count
   • Only whether the draft produces fluent text
   • Draft cost, target verification cost, accepted tokens and end-to-end latency under representative traffic
   • The number of tokenizer files
8. In exact speculative sampling, what happens when a proposed token is rejected?
   • The whole conversation is discarded
   • The target model is permanently changed
   • The rejected token is kept without verification
   • A correction step samples from the distribution needed to preserve the target model’s output distribution