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Kuramba Sampling Fine-Tuning
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Kufungidzira Sampling Verification
Speculative sampling uses a draft model to propose tokens and a target model to verify them.
Teerera kugwaro iriAI-yakarondedzerwa · ~2 min
Pa peji ino2 min verenga
Pfupiso
With the exact rejection-sampling correction, it preserves the target distribution; speedup depends on draft cost, acceptance, target verification and workload.
Kudzika Kwakadzika
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.
Kuitwa muNyika yeChokwadi
Kushandira 70B chat modhi ine 7B dhizaini modhi yekucheka mhinduro latency ingangoita muhafu neyakafanana kubuda mhando.
Medusa-maitiro misoro pane imwechete modhi inofanotaura akati wandei emangwana tokens, wobva wazvisimbisa pasina yakaparadzana dhizaini network.
Miti-yakavakirwa kufungidzira decoding iyo inopa akawanda mapazi kuenderera mberi uye inosimbisa iwo ese mune imwe chinangwa kupfuura.
Kumhanyisa kodhi-kupedzisa vabatsiri uko iyo dhizaini modhi inobata inofanotaurwa boilerplate iyo hombe modhi inosimbisa nekukurumidza.
Ramangwana reKufungidzira Sampling Verification
Kudhirodha kwekufungidzira kuri kuve kwakajairwa mumatura ekufungidzira. Misiyano mitsva inodonhedza iyo yakaparadzana dhizaini modhi: kuzvifungira kunoshandisa kukurumidza-kubuda kana mamwe ekufanotaura misoro (Medusa, EAGLE), kudhirowa kwemuti kunosimbisa kuenderera kwevamiriri kamwechete, uye kudhirodha kwekutarisa kunoenderana nefungidziro yen-giramu. Tarisira kusanganisa kwakasimba ne batching uye KV-cache manejimendi, hardware-inoziva dhizaini saizi, uye kushandiswa kwakakura mune latency-sensitive zvigadzirwa senge vabatsiri vekutaura uye maturusi ekukodha uko millisecond yega yega inoverengera.
Kuzvishandisa
Nei zvichikosha
- Kumhanya uye chiyero. Mutauro workflows inogona kufamba nekukurumidza pasina kupira kuenderana.
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Chenjera
- Chokwadi chehuroyi chinogona kupinda chinyararire mishumo, kuyerera kwetsigiro, kana tsvakiridzo.
- Kunzwa nekukasira kunogona kugadzira mhedzisiro isingaenderane pane zvikumbiro zvakafanana.
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Matanho anotevera
- Tsanangura chimiro chekubuda, toni, uye mhando zviyero usati waburitsa.
- Mhinduro dzepasi neakavimbika masosi pese pazvine basa.
- Chengetedza ongororo yekuongorora yemunhu kune yakakwira-stake zvinobuda.
- Tevera maitiro ekutadza uye dzidzisazve kukurudzira kana mafambiro ebasa nguva nenguva.
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Take the Speculative Sampling Verification quiz
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Chii chinonzi Speculative Sampling Verification?
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.
Ndeipi pfungwa huru kumashure kwekufungidzira sampling?
Iyo yakachipa yekudhirowa modhi inofembera akati wandei kumberi, uye inodhura yemhando yemhando inoatarisa ese mune imwechete inofambirana yekupfuura.
Sei kufungidzira sampling kusingaderedze kunaka kwekubuda?
Iyo yakagadziridzwa yekuramba-sampling kururamisa inovimbisa kuti tokeni dzinogamuchirwa dzinogovaniswa chaizvo senge iyo yakanangwa modhi yaizogadzira yega.
In exact speculative sampling, what happens when a drafted token is rejected?
Exact speculative sampling uses a rejection-sampling correction and discards the later draft suffix.
Under exact speculative sampling, what is guaranteed about the output distribution?
The rejection-sampling rule preserves the target distribution; this does not guarantee the same sampled string for each random seed.
What information does the target verification pass provide in exact speculative sampling?
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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