PyCharm: Training Your ML Models With Cadence

Cadence is a plugin introduced in PyCharm 2025.1 to merge local development with advanced cloud computing capabilities. It allows developers to run code on cloud hardware directly from PyCharm, alleviating complexities and setup associated with cloud computing. Cadence provides serverless computing on demand, reducing overhead with transparent and predictable per-second billing model removes the need for upfront hardware investments. The plugin allows users to upload and execute code as usual, with no modifications required, and handles adjustments on the backend. Debugging and deployment are done using the familiar PyCharm interface, with no additional learning curve. Cadence automatically synchronizes data to the cloud, allowing users to download experiment results directly in the IDE. It provides consistent replication of results, enabling continuous improvements. Users can choose from a wide range of cloud settings to scale resources according to project demands and schedule tasks simultaneously. The plugin is suitable for teams, allowing effortless sharing of setup configurations, results, and insights. Cadence can be tried for free with a $30 welcome credit by installing the plugin from JetBrains Marketplace or enabling it directly in PyCharm.