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adpt 0.13.6, published by Adaptive ML, is a lightweight command-line utility designed to let developers and data-science teams interact directly with the company’s Adaptive Platform from any terminal or scripted environment. Released as the sixth iterative build since the project’s debut, the tool exposes a concise set of sub-commands that authenticate against the platform, upload training data, launch distributed fine-tuning jobs, stream real-time logs, download resulting artifacts, and manage deployment endpoints without leaving the shell. Typical use cases include automating nightly retraining pipelines, embedding model updates into CI/CD workflows, provisioning sandboxed endpoints for A/B tests, and synchronizing on-premise datasets with cloud experiments. Because every operation is scriptable, infrastructure engineers can wire adpt into Make, PowerShell, or bash routines, while data scientists can fold it into Jupyter notebooks for rapid iteration. The executable is distributed as a single statically-linked binary for Windows, macOS, and Linux, eliminating dependency conflicts and simplifying containerized deployments. Version 0.13.6 refines OAuth token refresh, adds gzip compression for large artifact transfers, and introduces a dry-run flag that previews API calls before execution, changes that collectively cut upload times and reduce surprise quota consumption. Earlier releases progressively added support for multi-model projects, organization-level role checks, and concurrent job polling, making the current lineage well-suited to both individual researchers and enterprise MLOps stacks. As a command-line interface category application, adpt occupies the narrow but critical gap between browser-based dashboards and low-level REST scripting, offering reproducibility, speed, and remote automation in one coherent package. The software is available for free on get.nero.com, with downloads provided via trusted Windows package sources (e.g. winget), always delivering the latest version, and supporting batch installation of multiple applications.
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