InoteveraGaidhi rinotevera
Minimum Bayes Risk Decoding
Mutauro AI
Mutauro AI GUIDE
Contrast decoding inoburitsa mavara emhando yepamusoro nekubvisa maitiro emutauro mudiki, usina simba kubva kune iwo mukuru, wakasimba.
Teerera kugwaro iriAI-yakarondedzerwa · ~2 min
Inokwidziridza izvo nyanzvi inoziva uye iyo amateur inopotsa, ichideredza kudzokorora uye bland kubuda.
Contrastive decoding scores candidate tokens using an expert model and an amateur model, subtracting a weighted amateur log-probability from the expert score. It can suppress tokens that both models favor, including some generic or repetitive continuations. An adaptive plausibility constraint filters out tokens whose expert probability is too small relative to the expert’s highest-probability token. This constraint limits candidates; it does not guarantee coherent, grammatical, or truthful output. Output quality depends on the models, coefficient, threshold, prompt, and task, so evaluate the full generation. The method runs at inference time with two models and requires no additional training.
Kugadzira nyaya refu, isingadzokorore kana kuenderera mberi kwechinyorwa uko nucleus sampling inodonha kuita loop
Kubatanidza nyanzvi ye65B ine 1.5B amateur yekuvandudza chizvarwa chakavhurika pasina kunyatsogadzirisa.
Kuderedza kudzokororwa kwakashata mukupfupisa uye nhaurirano zvabuda
Kushanda sehwaro hweDoLa-maitiro ekuzvisiyanisa kudzikisa chokwadi chekufungidzira
Contrastive decoding yakakurudzira mhuri ye 'contrast at inference' nzira, kusanganisira DoLa (kusiyanisa yemuenzaniso wega wekare neanononoka maseketi kucheka kufungidzira) uye mutsauko-unoziva musiyano unosiyana uye usina magwaro akadzoserwa. Tarisira kubatanidzwa kwakasimba nekudzoreredza, zvibodzwa zvechokwadi, uye diki-amateur distillation, pamwe nekusanganiswa nekufungidzira decoding kuitira kuti maamateur atungamirire kunaka uye kukurumidze chizvarwa panguva imwe chete.
Tsamba yemahara
Nhatu dzakasimbiswa dzeAI nyaya mangwanani ega ega pakati pevhiki, dzakanyorwa neChirungu chakajeka. Yemahara zvachose, hapana ads.
Imwe email zuva rega rega revhiki. Bvisa kunyoresa kamwe chete. Hatimbotengese kana kugovera kero yako.
Zviedze iwe pachako
Mhinduro yepakarepo pamhinduro yega yega, uye chitupa chinogovaniswa chine ID inobatika kana wapedza kosi.
Tsigira dzidzo yemahara yeAI. AI Understanding ndeye 501(c)(3) isingabatsiri - hapana ads, hapana paywall, zvachose. Ita chipo
Contrast decoding inoburitsa mavara emhando yepamusoro nekubvisa maitiro emutauro mudiki, usina simba kubva kune iwo mukuru, wakasimba. Inokwidziridza izvo nyanzvi inoziva uye iyo amateur inopotsa, ichideredza kudzokorora uye bland kubuda.
Iyo amateur's log-mikana inobviswa kubva kune nyanzvi, kudzima zvikanganiso zvakarongeka (sekufarira ma tokens) ayo ese mamodheru anogovana.
Mhando dzose dziri mbiri dzinowanzoda-kunyanya-kuda kwepamusoro-frequency uye kudzokorora zviratidzo; kubvisa maamateur kunobvisa kurerekera kwakagovaniswa, kudzikisa sarudzo dzakapusa.
The constraint removes low-expert-probability tokens before contrastive scoring; it does not certify the coherence or truth of the final output.
Mumwe nemumwe anenge akwikwidza anopihwa zvibodzwa sezvo nyanzvi yelogi-mukana kubvisa akaremerwa neamateur log-mukana, mibairo tokeni iyo nyanzvi inosanoda.
DoLa inosiyanisa yekutanga nguva yemodhi (yekutanga-layer) uye yakakura (yanonoka-layer) fungidziro yekudzikisa kuona, kushandisa iyo yekusiyanisa pfungwa mukati memuenzaniso mumwe.
Ramba uchidzidza
Mamwe madhairekitori akasarudzirwa nyaya iyi
InoteveraGaidhi rinotevera
Minimum Bayes Risk Decoding
Mutauro AI