We present easy-to-use TensorFlow Hub sentence embedding models having good task
transfer performance. Model variants allow for trade-offs between accuracy and compute
resources. We report the relationship between model complexity, resources, and transfer
performance. Comparisons are made with baselines without transfer learning and to
baselines that incorporate word-level transfer. Transfer learning using sentence-level
embeddings is shown to outperform models without transfer learning and often those that …