{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/7"}],"enrichment":{"capability":"Maintains a structured index of machine learning model metadata (parameters, results, training data, paper links) stored as YAML, JSON, or markdown annotations, with optional integration to Papers with Code.","skillfed_tags":["ml-metadata","model-registry","abandoned"],"use_cases":["Publish a structured registry of trained models in a research repository or ML library for Papers with Code discovery","Maintain model metadata (FLOPs, parameters, training resources, results) in version-controlled YAML alongside code","Embed model documentation directly in markdown files and aggregate it into a searchable index","Track model performance metrics and results across datasets in a standardized, comparable format","Link model weights, papers, and code implementations in a single queryable source of truth"],"what_it_does":"model-index is a tool for organizing and publishing machine learning model metadata in a standardized, browsable format. It lets you define model information\u2014training parameters, results, dataset details, paper links, and code references\u2014in a single YAML file or spread across markdown files, then optionally upload that metadata to Papers with Code for community discovery.\n\nThe package is designed around flexibility: you can store metadata however is convenient (YAML, JSON, or markdown annotations), and model-index collects it into a unified index. All fields except model name are optional, and you can add custom fields beyond the standard ones. The main use case is maintaining a source-of-truth registry for a machine learning library or research project.","worth_installing":"No. The package is abandoned (no commits since June 2021, no releases since March 2021) and has received no maintenance or security updates in over four years. While install friction is low and the license is permissive, the lack of active maintenance means dependency compatibility cannot be guaranteed, and any bugs or breaking changes in its runtime dependencies will go unfixed. Use only if you have an existing project already relying on it and can maintain a local fork if needed."},"id":"model-index","links":{"html":"https://skillfed.io/packages/model-index","md":"https://skillfed.io/packages/model-index.md","pypi":"https://pypi.org/project/model-index/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2021-03-22","license_spdx":null,"license_treatment":"permissive","name":"model-index","python_support":"unspecified","summary":"Create a source of truth for ML model results and browse it on Papers with Code"},"popularity":{"monthly_downloads":234800,"position":9014,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.1.11"}