[{"data":1,"prerenderedAt":74},["ShallowReactive",2],{"term-m\u002Fmodel-registry":3,"related-m\u002Fmodel-registry":60},{"id":4,"title":5,"acronym":6,"body":7,"category":40,"description":41,"difficulty":42,"extension":43,"letter":44,"meta":45,"navigation":46,"path":47,"related":48,"seo":54,"sitemap":55,"stem":58,"subcategory":6,"__hash__":59},"terms\u002Fterms\u002Fm\u002Fmodel-registry.md","Model Registry",null,{"type":8,"value":9,"toc":33},"minimark",[10,15,19,23,26,30],[11,12,14],"h2",{"id":13},"eli5-the-vibe-check","ELI5 - The Vibe Check",[16,17,18],"p",{},"A model registry is the version control system for trained models instead of code. Every time someone fine-tunes or retrains a model, it gets logged with its metrics, its lineage, and a stage label like 'staging' or 'production.' Without one, you end up with a folder full of files named model_final_v2_ACTUALLY_final.pt and nobody knows which one is actually serving traffic.",[11,20,22],{"id":21},"real-talk","Real Talk",[16,24,25],{},"A model registry is a centralized system for versioning, storing, and tracking the lifecycle of trained models, recording metadata such as training data, hyperparameters, evaluation metrics, and deployment stage. Tools like MLflow Model Registry, Weights & Biases, and Vertex AI Model Registry let teams promote a specific model version from staging to production and roll back cleanly if a new version regresses.",[11,27,29],{"id":28},"when-youll-hear-this","When You'll Hear This",[16,31,32],{},"\"Promote v14 to production in the model registry once the eval gate passes.\" \u002F \"Nobody could tell which weights were live because we had no model registry.\"",{"title":34,"searchDepth":35,"depth":35,"links":36},"",2,[37,38,39],{"id":13,"depth":35,"text":14},{"id":21,"depth":35,"text":22},{"id":28,"depth":35,"text":29},"ai","A model registry is the version control system for trained models instead of code.","intermediate","md","m",{},true,"\u002Fterms\u002Fm\u002Fmodel-registry",[49,50,51,52,53],"Model","Fine-Tuning","Training","Model Card","Weights",{"title":5,"description":41},{"changefreq":56,"priority":57},"weekly",0.7,"terms\u002Fm\u002Fmodel-registry","6tVZPGq0hqbLFmtUt8ipfaPs9Lqx1tH4uYEjmFJDJCc",[61,65,68,71],{"title":49,"path":62,"acronym":6,"category":40,"difficulty":63,"description":64},"\u002Fterms\u002Fm\u002Fmodel","beginner","A model is the trained AI — the finished product.",{"title":52,"path":66,"acronym":6,"category":40,"difficulty":63,"description":67},"\u002Fterms\u002Fm\u002Fmodel-card","A model card is the nutrition label for an AI model.",{"title":51,"path":69,"acronym":6,"category":40,"difficulty":42,"description":70},"\u002Fterms\u002Ft\u002Ftraining","Training is the long, expensive process where an AI learns from data.",{"title":53,"path":72,"acronym":6,"category":40,"difficulty":42,"description":73},"\u002Fterms\u002Fw\u002Fweights","Weights are the numbers inside a neural network that determine what it knows and how it behaves — they're the AI's 'brain cells.",1792528100713]