Flambé: A Customizable Framework for Machine Learning Experiments
Jeremy Wohlwend, Nicholas Matthews, Ivan Itzcovich · 2019
Flambé is a machine learning experimentation framework built to accelerate the entire research life cycle.Flambé's main objective is to provide a unified interface for prototyping models, running experiments containing complex pipelines, monitoring those experiments in real-time, reporting results, and deploying a final model for inference.Flambé achieves both flexibility and simplicity by allowing users to write custom code but instantly include that code as a component in a larger system which is represented by a concise configuration file format.We demonstrate the application of the framework through a cuttingedge multistage use case: fine-tuning and distillation of a state of the art pretrained language model used for text classification. 1