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defar kodu IA ci wetu piscine
Poolside develops code-focused AI models and tools.
Déglul tegtal biiIA-nettali · ~1 min
Ci xët wii1 simili jàng
Résumé
Model capabilities, sizes, benchmark results, and deployment options depend on the named release.
Plongeur bu xóot
Poolside’s public model pages list code-oriented Laguna models and report benchmark results with source notes. The Laguna M.1/XS.2 technical report describes agentic evaluations using the Laude Institute’s Harbor framework and specifies the execution setup. It also lists 32K and 128K continued-pretraining sequence lengths for those versions. These details are version-specific. Code-execution feedback can measure specified test outcomes but does not establish correctness beyond those tests or prove security. Deployment claims should be verified against current documentation and terms.
Doxal ci àdduna dëgg
Use a code model to draft a function for developer review.
Run generated code against tests and inspect failures.
Check model documentation for release-specific benchmark setup.
Review enterprise data-handling and access requirements.
Ëlëgu defar kodu IA ci wetu piscine
Coding models are changing quickly. Evaluate the exact checkpoint and use case, apply tests and code review, and verify current enterprise controls.
Teg ko ci jëf
Lu tax mu am solo
- Pexem jaaykat. Kartu yoonu jaaykat yi ñooy wane man-man yi sa ekip mëna tabax ci kanam.
- Njëgg ak budget. Anamu jënd ak jaay ak tànneefi dugal dañu am njeexital ci njëg ak risk ci diir bu xawa yàgg.
- Risk ak kaaraange. Li liggéeyukaay bi di ñaax mooy tëral ni produit bi di doxee, kaaraange gi ak ubbeeku gi.
Moytul
- Koom-koomu ubbite mën na raw stabilite ci def liggéeyu defar dëgg.
- Njëg yi ci API wala coppite ci sàrt yi mën nañu dindi xalaat yi ci guddi gi.
- Dependence ci benn jaaykat dafay yokk njëgu tëjug ak migraasioŋ.
Jéego yi ci topp
- Saytu sa fournisseur yi nga jëfandikoo sa liggéey ak say done.
- Xoolaat mbir yu nëbbu, kaaraange ak sàrti yoon balaa ngay boole.
- Fexe am palaŋu fallback ci model yi wala jaaykat yi.
- Xool notu génne yi suko defee coppite yi ci kàrtu yoon du jaaxal ekip yi.
Weyal di banneexu
Bulletin bu amul fayda
Jàngal xibaar AI bu bes
Ñatti jaar-jaari IA yuñ firndeel bis bu nekk ci ayu-bis bi, ñu bind leen ci Àngle bu leer. Gratis ba fàww, amul yëgle.
Benn email bis bu nekk ci ayu-bis bi. Benn klik nga dindi abonemaa bi. Dunu musa jaay wala séddoo sa adres.
Nattal sa bopp
Take the Poolside AI Code Generation quiz
Feedback ci saasi ci bépp tontu, ak sertifikaa buñ mëna séddoo ak ID buñ mëna saytu soo jàllee ci njàng mi.
Jàppale njàngum IA te doo fay. AI Understanding mbootaay la buy def te Yàlla tax — amul yëgle, amul paywall, musul am. Defal ab sarax
Laaj yi ñuy faral di laaj
Luy defar kodu IA Poolside?
Poolside develops code-focused AI models and tools. Model capabilities, sizes, benchmark results, and deployment options depend on the named release.
Lan mooy pexem tàggat yaram biñ xamee Poolside?
Xeetu anamu siif bu Poolside mooy RLCEF, fu model bi di doxalee kode boppam ci test yi ak compilatër yi, ba noppi jàng ci ndax def nañu ko nimu waree.
What do Poolside’s Laguna models target?
Poolside describes its Laguna models as coding models aimed at software-development tasks.
Lan la Poolside di fësal ci kiliyaan yi?
Poolside dafay xool entreprise yi am hosting privé ak ci biir kër gi, suko defee kodu source bi du bàyyi environmaa kiliyaan bi.
What should a reader use to assess Poolside’s reported benchmark scores?
Poolside’s model page describes the provenance of displayed benchmark scores; results are specific to model and method.
Lan moo waral feedback ci jëfandikoo kode am solo lool ci tàggat xeetu kode?
Ginaaw compilatër yi ak test yi dañuy saytu njubte gi ci prograam bi, model bi mën na defar feedback yu bari yuñ defaree seen bopp te duñu soxla etiketu nit bu seer.
Weyal di jàng
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