temporal consistency

• Building LLMs: Evaluation & Deployment

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  The final installment in the series on building language models from scratch focuses on the crucial phase of evaluation, testing, and deployment. It emphasizes the importance of validating trained models through a practical evaluation framework that includes both quick and comprehensive checks beyond just perplexity. Key tests include historical accuracy, linguistic checks, temporal consistency, and performance sanity checks. Deployment strategies involve using CI-like smoke checks on CPUs to ensure models are reliable and reproducible. This phase is essential because training a model is only half the battle; without thorough evaluation and a repeatable publishing workflow, models risk being unreliable and unusable.

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  Read Full Article: Building LLMs: Evaluation & Deployment

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  Posted on

  Jan 2, 2026

  by

  NoiseReducer

  in

  Deep Dives, How-Tos

  Topics: language models, LLM, Deployment