Yekufungidzira Decoding Quiz

Mhinduro uye tsananguro zvinoonekwa paunenge uchitora bvunzo.

1. How does speculative decoding speed up generation from a large model?
   • Iyo diki dhizaini modhi inofungidzira akati wandei ma tokeni ayo hombe modhi inosimbisa mukuenderana
   • Kumanikidza muenzaniso kusvika hafu yehukuru hwayo zvachose
   • Kubvisa iyo yekutarisisa michina
   • Kudzidzira modhi pane mamwe data
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
   • Iyo dhizaini modhi inodzidziswa zvakare nekukurumidza
   • The matching prefix is kept, the target token is used at the mismatch, and later draft tokens are discarded
   • The goho quality zvachose degrades
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. Chii chinonyanya kutarisisa kukurumidza kubva pakufungidzira decoding?
   • Mwero wekugamuchirwa wefungidziro dzemodhi
   • Ruvara rweGPU
   • Hurefu hwezita remuenzaniso
   • Nguva yezuva
6. Chii chinonzi Medusa neEAGLE zvakafanana semafambiro?
   • Vanoda quantum hardware
   • Ivo vanobvisa kudiwa kweyakasiyana yakamira dhizaini modhi
   • Vanodzima iyo inotarirwa modhi
   • Vanoshanda chete pamifananidzo
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