Weekly round-up: Deploy your ML model, step-by-step
The model deployment modal is gone, replaced with a full page of instructions to help you check off the prerequisite steps then deploy your model to Baseten with confidence. Dynamic examples across modeling frameworks give you paste-able deployment scripts to use in your code, while the “Import from SageMaker” tab helps you establish a data connection then import your SageMaker models to Baseten.
Along with this on-page guidance, we now have seven new end-to-end model deployment and invocation examples as Google Colab notebooks that you can run from your browser or download. Try deploying models built with HuggingFace, PyTorch, scikit-learn, and more!
Fix errors faster in code files
Scientists estimate that there are 10 quintillion bugs alive on the planet at any given time. Make sure none of them are lurking in your code with new error messages when you try to save invalid syntax in code files.
