Finding the Words to Say: Hidden State Visualizations for Language Models
By visualizing the hidden state between a model's layers, we can get some clues as to the model's "thought process".
Figure: Finding the words to say
After a language model generates a sentence, we can visualize a view of how the model came by each word (column). Each row is a model layer. The value and color indicate the ranking of the output token at that layer. The darker the color, the higher the ranking. Layer 0 is at the top. Layer 47 is at the bottom.
Model:GPT2-XL
Part 2: Continuing the pursuit of making Transformer language models more transparent, this article showcases a collection of visualizations to uncover mechanics of language generation inside a pre-trained language model. These visualizations are all created using Ecco, the open-source package we're releasing