Word
Word embeddings dafay soppi baat yi ci limu nimero yi suko defee baat yi ñuy jëfandikoo ci anam wu noonu mujjee jegewaale ci benn espace math.
Résumé
They are the foundation that lets a computer treat language as something it can measure and compare.
Plongeur bu xóot
Baatu embedding dafay màndargaal baat bu nekk ni vecteur — limu nimero yu gudd, lu bari 100 ba 300 ci model yu yàgg yi. Nimero yooyu dañu leen jàngee ci mbind yu bari, soo seetlu baat yi feeñ ci seen biir. Word2vec, bi Tomas Mikolov ak ay naataangoom génne ci Google ci 2013, dafa siiwal xalaat bi ci ñaari pexe tàggat: skip-gram (xam luy waaja am ci baat biñ bëgga wax) ak CBOW (xam luy waaja am ci dëkkandoo yi). GloVe bu Stanford moo ci topp ci 2014, tabax ay vecteur yu bawoo ci lim yiy boole baat yi ci àdduna bi. Resultaa bi siiw mooy ni math vecteur dafay jàpp lu muy tekki: buur bi dindi góor gi yokk jigéen ji daanu ci wetu reine bi. Royuwaayi làkk yu mag yi tay dañu dem lu gëna sori, jàng embeddings ngir ay token yuy soppiku ak contexte.
Gis-gis xarala
Embedding yi dañu leen di jàng, duñu kode loxo. Bu ñuy tàggat, model bi dafay yamale vecteur bu baat bu nekk suko defee baat yiy feeñ ci contexte yu nuróo ñu gëna jegewaale, ñu natt ko ci nuru cosine (angle bi am ci digganté vecteur yi). Word2vec ak GloVe dañuy jox baat bu nekk benn vecteur bu takku, frase bi du ci dara. Modèle transformateur yu bees yi dañuy tàmbalee ci embedding token ba noppi ñu soppali ko layer par layer, kon benn baat bu melni 'bànk' dafay am vecteur yu wuute ci 'banku dex' ak 'banku dencukaay' - loolu lañuy woowe embedding contextuel.
njeextalu pexe
Gaawaay ak yaatuwaay
Liggéeyukaay yi ci làkk yi mën nañu gëna gaaw te duñu yàq deggoo gi.
Dugg ak yegg
Dafay yaatal jëfandikoo gi ci làkk yi ak ci anam yi ñuy jokkoo.
dogal yu gëna leer
Ekip yi mën nañu gëna yàgg ci àtte ci jamono ji otomatisation di liggéey ci baamtu.
Ëlëgu Embeddings Word
Embedding static benn vecteur ci baat bu nekk leegi dafay nuru konsept jàngale ak baseline bu gaaw; sistemu defar yi deñuy jëfandikoo ay xeetu transformatër yu jëm ci xeetu transformatër yi. Frontiere bi gëna mag mooy dugal ay frase yu mat sëkk, ay këyit, ay nataal, ak ay audio yuñ boole ci benn barab buñ bokk, loolu mooy dooleel seetlu semantik ak defar-augmented generation. Xaarandil ni embeddings yi dina ñu gëna xéewale ci ordinatër, lakk yu bari ci default, ak lu am solo ci ni sistemu IA yi di gisee xibaar bu am solo moo gën ñu ko xam ci seen biir.
Doxal ci àdduna dëgg
Motëri seetlu semantik yiy delloo dokimaa yu méngoo ak li laaj bi di tekki, te baña yam ci baatu-caabi yi méngoo.
Sistem yiy xelal nit ñi ñuy xelal produit wala article yu noonu mel ci méngale seeni vecteur yuñ samp.
Dooleel jikkoom-yokkum (RAG), fu chatbot dugal sa laaj ngir génne mbind yi gëna am solo ci base xam-xam.
Clustering ak deduplication, lu melni boole ay këyit yuy jàppale yu nuru wala xibaar ci jegewaale vecteur.
Risk yi ak balustrade yi
Lépp lu jaarul yoon mën na dugg ci rapoor yi, jàppale ci liggéey bi, wala ci njariñu gëstu bi.
Sensibilite bu gaaw mën na jur njariñ yu wuute ci laajte yu noonu mel.
Done yu am solo mën nañu feeñ sudee seytu jëfandikoo gi néew doole.
Roadmap ngir samp gi
Mandargal formaa génne gi, melokaan bi, ak standard kalite yi laata ngay dugal ko.
Tontu yu am solo ak balluwaay yu wóor saa yu dëggu bi di am solo.
Fexeel am barabu xool nit ñi ngir am njariñ yu am solo.
Toppal anami gacce yi ak di faral di tàggataat ay laaj wala def-liggéey.
Weyal di banneexu
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Gis bi ci topp
Mbind yuñ dugal
Laaj yi ñuy faral di laaj
What is Word Embeddings?
Word embeddings dafay soppi baat yi ci limu nimero yi suko defee baat yi ñuy jëfandikoo ci anam wu noonu mujjee jegewaale ci benn espace math. Mooy fondaasioŋ biy may ordinatër bi mu jàppee làkk ni lu mu mëna natt ak méngale.
Luy baat buy tënk?
Embedding dafay boole ab baat ci limu nimero yi (vecteur) suko defee baat yi ñuy jëfandikoo ñuy mujjee nekk ci wetu seen biir ci barabu nimero bi.
naka la model yu melni word2vec di jàngee lu baat bi di tekki?
Word2vec learns from context: words that appear in similar surrounding text get similar vectors. Amul benn tegtal bu nit soxla.
Lan mooy wuute bu mag bi am ci digganté word2vec/GloVe ak li nekk ci biir model transformateur yu bees yi?
Embeddings yu yàgg yi dañuy jox benn vecteur baat bu nekk, frase bi du ci dara; transformatër yi dañuy yamale vecteur bi ci anam wi ko wër, kon 'bànk' dafay wuute ci jëfandikoo gi.
Ban liggéey moo gëna aju ci méngale vecteur yuñ samp?
Seetug semantik dafay dugal laaj bi ak këyit yi, ba noppi mu gis vecteur yi gëna jege, mu delloosi resultaa yi méngoo ak li ñuy tekki, du baat yi gëna jub.
Lu tollu ci ñaata lim (dimension) la word2vec wala GloVe bu yàgg di jëfandikoo ci baat bu nekk?
Embeddings static yu yàgg yi dañuy faral di jëfandikoo ci diggante 100 ba 300 dimension, doy ngir jàpp diggante yu am solo te baña nekk lu jafe jëfandikoo.