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Tools for training models to interface with external APIs and functions through structured output definitions.
Distinguishing note: Specifically targets the training of models to handle function calling and tool execution, distinct from general model fine-tuning.
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This project is a comprehensive framework for the entire lifecycle of transformer-based language models, supporting everything from foundational pretraining to specialized deployment. It provides a modular toolkit for defining neural network architectures, managing data preparation pipelines, and executing training routines across various scales. The framework is designed to handle the full model development process, including supervised fine-tuning, behavioral alignment, and the integration of agentic capabilities. What distinguishes this framework is its focus on efficient training and adva
The framework supports tool calling integration by training models to recognize and execute external function calls through structured tool definitions within multi-turn conversation datasets.