kleveross/klever-model-registry
Cloud Native Machine Learning Model Registry
This project helps MLOps engineers and machine learning practitioners manage, version, and deploy their machine learning models in a cloud-native environment. It takes trained models (like TensorFlow SavedModel, ONNX, or Keras H5) and helps organize them, convert them between formats, and then serve them for predictions. The end-user is typically an MLOps engineer or a data scientist responsible for deploying and maintaining models in production.
No commits in the last 6 months.
Use this if you need a centralized system to manage the lifecycle of your machine learning models, including versioning, format conversion, and serving, especially within a Kubernetes environment.
Not ideal if you are looking for a simple tool to train models or if your organization does not use Kubernetes for deployment.
Stars
82
Forks
25
Language
Go
License
Apache-2.0
Category
Last pushed
Jan 12, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/mlops/kleveross/klever-model-registry"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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