We present the Language Interpretability Tool (LIT), an open-source platform
for visualization and understanding of NLP models. We focus on core questions
about model behavior: Why did my model make this prediction? When does it
perform poorly? What...
Transformer architectures show significant promise for natural language
processing. Given that a single pretrained model can be fine-tuned to perform
well on many different tasks, these networks appear to extract generally useful