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Google Fonts

Sébastien Merour
publié le 27/03/2020 à 17h47 | modifé le 25/04/2020 à 16h54
Catégorie : Front-End | Commentaires (64963)
Google Fonts
Description

Google Fonts est une service d'hébergement de polices de caractères créé en 2010. Ce service, créé par Google, permet d'afficher des polices de caractères spécifiques sur un site web, grâce à un fichier CSS disponible sur le site de Google Fonts. Les développeurs peuvent faire appel à ce fichier CSS en mode "embed", ou bien en téléchargeant le fichier CSS pour l'intégrer ensuite en local sur le site. Il est préférable de l'utiliser en mode "embed" pour ne pas ralentir l'affichage du site.

Fonctionnalités
Police d'écriture
Année de création
2010
Licence
SIL Open Font License 1.1 / Apache License
Langage
CSS
Liens
Aux dernières nouvelles
960 polices de caractères gratuites. Polices populaires : Open Sans, Roboto, Lato, Slabo, Oswald and Lobster.
64963 Commentaire(s)
  1. user
    Kimsearf
    14/10/2026 à 10h56  commentaire modifé
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    FelixSnigo
    14/10/2026 à 10h55  commentaire modifé
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    Alecphymn
    14/10/2026 à 10h49  commentaire modifé
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  4. user
    AI_Engineer_jary
    14/10/2026 à 10h42  commentaire modifé
    An AI feature should have a defined response when one dependency becomes unavailable. Repeating the same request can amplify load and still return no useful result. An AI reliability design should separate retryable failures from conditions that require a user message or manual path. Decide which functions can continue without generation. Search results may remain available while summarization is paused, and a draft action can wait instead of executing with missing data. https://ai-software-development.net A production AI workflow also needs timeouts, bounded retries and circuit breaking outside the model. Recovery tests have two jobs. They must verify that queued work is not duplicated and that users can tell whether an action completed.
  5. user
    ML_Systems_jary
    14/10/2026 à 10h42  commentaire modifé
    An AI development partner should be evaluated against the work that survives the demo. Ask how the team will define acceptance tests and handle unavailable data. It should also explain model version records and the transfer of operational ownership. A polished prototype says little about monitoring or rollback behavior. AI development partner criteria outlines the service context. Before signing, request a plain explanation of prompt ownership, then ask where deployment code and evaluation sets will be stored. The reference at https://ai-software-development.net points to related engineering services. Compare that scope with custom AI development requirements, then verify how changes will be approved after release. The strongest proposal names dependencies and failure conditions without promising a model outcome before the data has been reviewed.
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