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Réjection de échantillonnage de rejection
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Speculative sampling uses a draft model to propose tokens and a target model to verify them.
Déglul tegtal biiIA-nettali · ~2 min
With the exact rejection-sampling correction, it preserves the target distribution; speedup depends on draft cost, acceptance, target verification and workload.
Autoregressive generation is slow because each token needs a full forward pass of a huge model. Speculative sampling fixes this by pairing a cheap draft model with the expensive target model. The draft proposes a short run of tokens (say 4-8); the target then scores all of them in one parallel forward pass. A modified rejection-sampling rule accepts the longest prefix that is consistent with the target's own distribution and resamples at the first rejected position. Because acceptance is probabilistic and corrected, the final token stream is provably distributed exactly as if the target had generated alone, no quality loss. Speedups vary with draft cost, acceptance rate, target verification, batching and hardware. A parallel verification pass can confirm multiple tokens, but is not free.
Liggéey ci xeetu waxtaan 70B ak xeetu projet 7B ngir dagg latency tontu ci genn-wàll ak kalite génne bu nuróo.
Medusa-style boppu ci benn model di wax luy waaja am ci ay token yu bari, ba noppi di leen xool ndax amul benn reso bu wuute.
Decodage speculatif bu sukkandiko ci garab, di proposer ay branching yu bari yuy wéyal, ba noppi di leen xool ñépp ci benn pass target.
Gaawaale ndimmbalu yeggali kode fu modelu projet bi di jëfandikoo plaque chaudière buñu mëna wax luy waaja am, te model bu mag bi dafay gaaw firnde.
Dekodaas speculatif mingi nekk standard ci stack inference yi. Variante yu bees yi dañuy bàyyi xeetu projet bu wuute: xalaat sa bopp dafay jëfandikoo boppu génn bu teel wala boppu prediction bu gëna bari (Medusa, EAGLE), projet bu sukkandiko ci garab dafay firndeel wéyal kàndidaa yu bari ci benn yoon, ak dekodaasu kanam buy parallelize n-gram guesses. Xaarandil lëkkaloo bu gëna dëgër ak yoriinu batching ak KV-cache, dimensionnement bu xam hardware bi, ak jëfandikoo bu gëna yaatu ci produit yu sensible ci latency lu melni assistant chat ak jumtukaayi codage fu millisecond bu nekk am solo.
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Speculative sampling uses a draft model to propose tokens and a target model to verify them. With the exact rejection-sampling correction, it preserves the target distribution; speedup depends on draft cost, acceptance, target verification and workload.
Benn modelu projet bu yomb dafay xayma ay token yu bari ci kanam, ba noppi modelu target bu seer bi dafay saytu leen ñépp ci benn pass forward parallèle.
Coppite biñu bañ-sampling correction dafay garanti jetons yiñ nangu ñu séddale leen ci anam wi model biñ bëgga defaree kese.
Exact speculative sampling uses a rejection-sampling correction and discards the later draft suffix.
The rejection-sampling rule preserves the target distribution; this does not guarantee the same sampled string for each random seed.
The target pass scores the draft proposals and supplies target probabilities used by the acceptance rule and residual correction; it has a computation cost.
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Ci bi mu melGis bi ci topp
Réjection de échantillonnage de rejection
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