Tag Archives: manages

Do you feel risky training your language model on limited data? Meet SILO: A new language model that manages risk-performance trade-offs during inference

Sparse probe employed in 'Finding neurons in the haystack' initiative at MIT, Harvard and Northeastern University

Legal concerns have been raised about massive language models (LMs) because they are often trained on copyrighted content. The inherent trade-off between legal risk and model performance is at the heart of this topic. Using only permissioned or publicly available data for training has a serious negative impact on accuracy. Since common LM corpora include… Read More »