Kuiz Penyahkodan Spekulatif

Jawapan dan penjelasan muncul semasa anda mengambil kuiz.

1. How does speculative decoding speed up generation from a large model?
   • Model draf kecil meneka beberapa token yang disahkan oleh model besar secara selari
   • Memampatkan model kepada separuh saiznya secara kekal
   • Mengeluarkan mekanisme perhatian
   • Melatih model pada lebih banyak 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
   • Model draf dilatih semula serta-merta
   • The matching prefix is kept, the target token is used at the mismatch, and later draft tokens are discarded
   • Kualiti keluaran merosot secara kekal
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. Apakah yang paling langsung menentukan kelajuan daripada penyahkodan spekulatif?
   • Kadar penerimaan tekaan model draf
   • Warna GPU
   • Panjang nama model
   • Masa hari
6. Apakah persamaan Medusa dan EAGLE sebagai pendekatan?
   • Mereka memerlukan perkakasan kuantum
   • Mereka menghapuskan keperluan untuk model draf kendiri yang berasingan
   • Mereka memadam model sasaran
   • Mereka hanya berfungsi pada imej
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