Classification of LLM Scaling
LLM scaling strategies, which aim to enhance performance and compute capabilities, can be categorized based on the model's lifecycle stage. The three primary types are Pre-training Scaling, Fine-tuning Scaling, and Inference-time Scaling.
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Ch.5 Inference - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Learn After
Inference-Time Scaling
A development team is enhancing a large language model through a series of steps. First, they train a new, larger version of the model from scratch on a massive, general-purpose text corpus. Next, they adapt this new model for a specific task by continuing its training on a smaller, curated dataset of customer service conversations. Finally, when the model is deployed, they improve its response quality by using a technique that generates multiple potential answers and selects the best one, a pro
Match each description of a large language model enhancement strategy with its correct classification based on the model's lifecycle stage.
LLM Enhancement Strategy Analysis