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Defining which data sources are used for training, validation, and testing phases.
Distinct from Training Datasets: Moves from the general concept of a training dataset to the specific act of defining phase splits.
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Oumi is a comprehensive large language model development platform designed for synthesizing data, fine-tuning models, and running performance evaluations. It serves as a unified environment for the entire model lifecycle, encompassing a training and fine-tuning suite, an evaluation framework, and tools for synthetic data generation and model distillation. The platform is distinguished by its iterative, failure-driven synthesis approach, which analyzes model weaknesses during evaluation to generate targeted training data. It utilizes an LLM-based judge framework to programmatically score respo
Assigns specific data sources for training, validation, and testing phases to ensure structured learning.