Modelbit works with the latest and greatest, from Segment-Anything to OWL-ViT; from LLaMa to GPT; and of course all your custom models built in any technology from Tensorflow to PyTorch.
Learn MoreDeploying your model is as simple as calling mb.deploy right from your notebook. No need for special frameworks or code rewrites.
Models are deployed directly into your data warehouse, where making a model inference is as easy as calling a SQL function!
Modelbit models become REST APIs in the cloud. Your team can call them from websites, mobile apps, and IT applications.
Modelbit is backed by your git repo, where data is secure and version controlled, and CI/CD runs when changes are deployed.
Each model is deployed to a fully custom, isolated Docker container, complete with load balancing, logging and disaster recovery. ML models deployed with Modelbit can be called as a REST endpoint directly from your product.
Learn MoreUse Modelbit to deploy ML models into your cloud for maximum convenience paired with maximum security. Reach out to us request access.
Request AccessModelbit is backed by your git repo. GitHub, GitLab, or home grown. Code review. CI/CD pipelines. PRs and Merge Requests. Bring your whole git workflow to your Python ML models.
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