Tool-use capabilities in language models improve significantly when trained during mid-training with targeted synthetic data, rather than waiting until post-training—similar to how math and reasoning skills benefit from dedicated training phases.
MidTool is a data synthesis pipeline that creates training data for teaching language models to use tools effectively during mid-training (the stage between pretraining and fine-tuning).