• Researchers improve large language models through efficient pre-training and scaling.
  • Cerebras-GPT models show state-of-the-art training efficiency on both pre-training and downstream objectives.

Key terms:

  • Pre-training: initial training phase of a language model using a large dataset
  • Scaling: increasing the size and complexity of a model to improve its performance
  • Cerebras-GPT: a family of efficient language models with improved performance
  • HuggingFace: a platform for sharing and using pre-trained language models


Research Tools HuggingFace Cerebras-GPT Open Compute Optimal Power Law Scaling Hyperparameter Predictability Compute Optimal Reproducibility Large Models