Training a 360M Parameter Model with Performance Discipline
Pretraining SmolLM-360M on a single A100 GPU within a 30-hour window, focusing on feasibility analysis, throughput measurement, and hardware efficiency optimization.
Pretraining SmolLM-360M on a single A100 GPU within a 30-hour window, focusing on feasibility analysis, throughput measurement, and hardware efficiency optimization.
Exploring whether language model agents can enhance the performance of other LLM agents through a meta-benchmark approach.