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Yakareba Context vs RAG
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Long-Context Modelling
Yakareba-context modelling inodzidza magadzirirwo emitauro yeTransformer-based magadzirirwo akakura ekuisa akatevedzana.
Teerera kugwaro iriAI-yakarondedzerwa · ~2 min
Pa peji ino2 min verenga
Pfupiso
Hwindo rechimiro chakashambadzirwa chemodhi chiyereso chechiratidzo, nepo kushandiswa kunoshanda kunoenderana nekutarisisa komputa, kubata chinzvimbo uye kudzoreredza kuita mukati mekuisa.
Kudzika Kwakadzika
Iyo Transformer yakajairwa yekuzvitarisa inokokorodza kupindirana munzvimbo dzetokeni, uye kutarisisa kwayo kunowedzera kukura nequadratically nekutevedzana kureba. FlashAttention ndeye chaiyo, IO-inoziva kutarisisa algorithm inoshandisa tiling kuderedza kuverenga uye kunyora pakati peGPU ndangariro mazinga; haibvisi hukama huri pasi pekutarisa. Rotary chinzvimbo embeddings (RoPE) encode tokeni nzvimbo. Position Interpolation inzira yakanangana nebepa inodzoreredza zvinzvimbo kuwedzera mamiriro muRoPE-yakavakirwa pretrained modhi uye inoongororwa pamabasa akadai sekudzoreredza uye kupfupisa kwezvinyorwa-refu. Iyo Yakarasika muChidzidzo chepakati inowana chinzvimbo-sensitive performance pane refu-context QA uye kudzoreredza mabasa. RULER inowedzera kudzoreredza tsono neakawanda-hop kutsvaga uye kuunganidza. Prompt Cache zvidzidzo zvekushandisa zvakare kutarisa kune zvinogoneka kushandiswa kukurumidza zvikamu. Idzi inzira dzakasiyana dzine fungidziro dzakasiyana; miganho yakareba yemamiriro ezvinhu haite nechokwadi chekushandiswa kwechokwadi kweruzivo rwese rwunopihwa.
Kuitwa muNyika yeChokwadi
Mubvunzo wegwaro rekuyedza uchipindura nendima dzakakodzera wakaendeswa kunzvimbo dzakasiyana mumamiriro ezvinhu.
Kuongorora marefu-mamiriro emhando pane akawanda-hop ekutsvaga uye aggregation mabasa, kwete chete chokwadi-chekudzosa kukurumidza.
Kushandisa IO-aware attention kernels kuderedza kutarisisa-ndangariro traffic.
Kushandisazve kutarisa kwezvikamu zvekukurumidza zvinodzokororwa uko nzira yekushumira inoitsigira.
Ramangwana Rekutevedzera Mamiriro Akareba
Mamiriro ezvinhu anoshanda anofanira kuyerwa nemiedzo yakanangana nebasa pazvinzvimbo uye kureba kwekutevedzana. Iyo Yakarasika pakati uye RULER zvidzidzo zvinoratidza kuti nei hwindo rakataurwa remamiriro ega risiri humbowo hwakakwana hwekudzoreredza kana hunhu hwekufunga. Rondedzera modhi, basa, kureba, latency uye mutengo kana uchienzanisa nzira dzemamiriro.
Kuzvishandisa
Nei zvichikosha
- Kumhanya uye chiyero. Mutauro workflows inogona kufamba nekukurumidza pasina kupira kuenderana.
- Svika uye svika. Inopamhidzira kupinda mumitauro yese nemataera ekutaurirana.
- Sarudzo dzakajeka. Zvikwata zvinogona kupedza nguva yakawanda pakutonga uku otomatiki ichibata kudzokorora.
Chenjera
- Chokwadi chehuroyi chinogona kupinda chinyararire mishumo, kuyerera kwetsigiro, kana tsvakiridzo.
- Kunzwa nekukasira kunogona kugadzira mhedzisiro isingaenderane pane zvikumbiro zvakafanana.
- Sensitive text data inogona kuburitswa kana zvidhiraivho zvisina kusimba.
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.
Ramba Uchiongorora
Tsamba yemahara
Tora iyo yemazuva ese AI pfupiso
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
Take the Long-Context Modeling quiz
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
Mibvunzo inowanzo bvunzwa
Chii chinonzi Long-Context Modelling?
Yakareba-context modelling inodzidza magadzirirwo emitauro yeTransformer-based magadzirirwo akakura ekuisa akatevedzana. Hwindo rechimiro chakashambadzirwa chemodhi chiyereso chechiratidzo, nepo kushandiswa kunoshanda kunoenderana nekutarisisa komputa, kubata chinzvimbo uye kudzoreredza kuita mukati mekuisa.
Chii chinonzi 'context window' yemuenzaniso?
Hwindo remamiriro ekunze ndiyo bhajeti rechiratidzo iyo modhi inogona kuverenga uye kufunga panguva imwe chete mukupfuura kumberi.
Sei kuzvitarisira kwakajairwa kuchidhura kune zvigadzirwa zvenguva refu?
Kuzvitarisa kunoenzanisa chiratidzo chega chega kune chimwe chiratidzo, saka zvikero zvinodhura seO(n squared) mukutevedzana kureba n.
Dambudziko re'kurasika pakati' nderei?
Zvidzidzo zvinoratidza kudzoreredza kwechokwadi dips yezvinyorwa zvakaiswa pakati penguva refu, saka kureba chete hakuvimbisi kurangarira.
Chii chinonzi FlashAttention inonyanya kuvandudza?
FlashAttention inoverengera kutarisisa mumatiles pasina kuita iyo yakazara yekutarisisa matrix mundangariro, kurerutsa mutengo wekurangarira wekutevedzana kwakareba.
Ibasa rei rinoitwa nerotary position embeddings (RoPE) mumhando dzenguva refu?
RoPE encodes chinzvimbo. Position Interpolation ndiyo imwe nzira chaiyo inodzoreredza zvinzvimbo kuti iwedzere yakaedzwa RoPE-yakavakirwa modhi; mhedzisiro ndeye modhi- uye inoenderana nebasa.
Ramba uchidzidza
Mazano anoenderana
Mamwe madhairekitori akasarudzirwa nyaya iyi