DanLing is an open-source Python library designed to help machine learning researchers and engineers build flexible neural network training workflows. It provides utilities for runners, logging, checkpointing, and custom training loops, reducing repetitive code and supporting advanced research needs.
In the Data science & ML workbench space, DanLing takes a focused approach. It focuses on reducing boilerplate and increasing flexibility for machine learning researchers building custom training workflows. It is built as an open-source project for machine learning researchers and engineers. DanLing is open source. DanLing is available on the web and the command line.
It is developed by Zhiyuan Chen, and the product first shipped in 2022. Development happens publicly on GitHub with 23 stars and 28 commits in the last 90 days. Key capabilities include flexible runners, logging utilities, and checkpointing. The interface is available in English and Chinese.
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