{"id":125519,"date":"2025-05-23T15:05:12","date_gmt":"2025-05-23T13:05:12","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/mistral-ai-opublikoval-devstral-bolshuyu-yazykovuyu-model-dlya-raboty-s-kodom"},"modified":"2025-05-23T15:05:12","modified_gmt":"2025-05-23T13:05:12","slug":"mistral-ai-opublikoval-devstral-bolshuyu-yazykovuyu-model-dlya-raboty-s-kodom","status":"publish","type":"post","link":"https:\/\/prohoster.info\/et\/blog\/novosti-interneta\/mistral-ai-opublikoval-devstral-bolshuyu-yazykovuyu-model-dlya-raboty-s-kodom","title":{"rendered":"Mistral AI on avaldanud Devstral'i, suure keelemudeli koodi t\u00f6\u00f6tlemiseks.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Mistral AI ettev\u00f5te tutvustas suurt keelemudelit Devstral, mis on optimeeritud tarkvaraarenduse probleemide lahendamiseks. Erinevalt t\u00fc\u00fcpilistest AI mudelitest \u00fcletab Mistral AI \u00fcksikute funktsioonide kirjutamise ja koodi t\u00e4iustamise ning pakub v\u00f5imalusi, mis v\u00f5imaldavad anal\u00fc\u00fcsida ja kontekstitada (m\u00e4\u00e4ra m\u00e4\u00e4ratlust ja t\u00f6\u00f6loogikat) suuri koodibaase, m\u00e4\u00e4rata komponentide vahelisi seoseid ja tuvastada keerulistes funktsioonides peituvaid vigu. <\/p>\n

Mudel katab 23,6 miljardit parameetrit, arvestab konteksti 128 000 tokeni ulatuses ja on avaldatud Apache 2.0 litsentsi alusel. Devstrali allalaetav arhiiv on 47 GB ja sobib kasutamiseks kohalikes s\u00fcsteemides \u2014 mudeli k\u00e4itamiseks piisab \u00fchest arvutist, millel on NVIDIA GeForce RTX 4090 graafikakaart ja 32 GB RAM-i. Mudelit saab kasutada avatud t\u00f6\u00f6riistades SWE-agent ja OpenHands vigade automaatseks parandamiseks, koodi anal\u00fc\u00fcsimiseks ja muudatuste tegemiseks. <\/p>\n

S\u00fcsteemi saab kasutada konkreetsete probleemide (issue) lahendamiseks GitHubis ja see \u00fcletab teisi projekte testkomplektis SWE-Bench Verified, mis kontrollib t\u00fc\u00fcpiliste koodiprobleemide lahendamise \u00f5igsust (pakutakse 500 testi, mis p\u00f5hinevad reaalsetel veateadetel GitHubis). Selles testis saavutas Devstral mudel 46,8%, samas kui mudel Claude 3.5 Haiku sai 40,6%, SWE-smith-LM 32B \u2014 40,2% ja GPT-4.1-mini \u2014 23,6%. Muude hulgas \u00fcletas Devstral ka suurmudeleid, nagu Deepseek-V3-0324 671B (38,8%) ja Qwen3 232B-A22B (34,4%), mis katab sadu miljardeid parameetreid.
\n
Allikas: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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