model-registry

🌀 𝗧𝗵𝗲 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝟳-𝗦𝘁𝗲𝗽𝘀 𝗠𝗟𝗢𝗽𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 | 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟𝗘 & 𝗠𝗟𝗢𝗽𝘀 for free by designing, building and deploying an end-to-end ML batch system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 2.5 𝘩𝘰𝘶𝘳𝘴 𝘰𝘧 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 & 𝘷𝘪𝘥𝘦𝘰 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴

🐶 A tool to package, serve, and deploy any ML model on any platform. Archived to be resurrected one day🤞

An Open-source, self-hosted AI model hub with Hugging Face compatibility, accelerating vLLM/SGLang performance.

A curated list of awesome open source tools and commercial products for ML Experiment Tracking and Management 🚀

🏷️ Git Tag Ops. Turn your Git repository into Artifact Registry or Model Registry.

Stop trusting your pipeline. Verify it; visually on a canvas or in Python. Self-hosted platform + library. Now, you can be able use it in Databricks and MLFlow with bundle option.

Community-maintained registry of AI/LLM model configurations - pricing, features, and limits across 19 providers and 1000+ models

MLOps for deploying a Credit Risk model

Community-maintained JVM marker JAR catalog for local AI models

A simple app to help you find relevant machine learning papers to read.

Self-hostable content-addressed storage for AI models, datasets, containers, and build artifacts with Git LFS, OCI, Bazel HTTP, Huggingface, and Xet frontends

Production-grade MLOps: Model deployment, monitoring, feature stores, and ML pipelines for real-world AI systems.

An end to end ML project. Using MLflow for experiment tracking and model registry. Prefect for workflow orchestration. S3 for artifacts storage. AWS Lambda/ ECR for serverless model serving. AWS REST API gateway as endpoint to lambda function. GitHub Actions for CI/CD.

Open-source ML model registry and inference platform with versioned artifacts, predictions, metrics, and observability.

🧙‍♂️ A professional machine learning GUI for scientists, developers & students — powered by PySide6 & scikit-learn. 📊 Load data, preprocess, train, evaluate, and predict — all without writing code. ⚡ Includes AutoML, hyperparameter tuning, model registry, experiment tracking, and a plugin system.

Hopsworks Machine Learning Api 🚀 Model management with a model registry and model serving

PolicyBind is an AI Policy-as-Code platform that enables organizations to govern AI usage through a unified model registry, real-time token-based access control, and automated compliance reporting for frameworks like the EU AI Act and NIST AI RMF.

Part of the Hydrosphere.io project.

Research-to-production AI model release control plane connecting post-training experiments, baseline/candidate evaluation, regression analysis, safety/correctness checks, CI release gates, production telemetry, and evidence-linked SHIP · INVESTIGATE · HOLD decisions.

Open registry of large-language-model metadata — identity, authorship, modalities, context/output limits, capabilities & lifecycle dates as one machine-readable models.json validated by JSON Schema. CC BY 4.0.