We present Inseq, a Python library to democratize access to interpretability analyses of sequence generation models.
An interpretability framework to detect and attribute context usage in language models' generations
An open-source library to democratize access to model interpretability for sequence generation models
We present ETC-NLG, an approach leveraging topic modeling annotations to enable fully-unsupervised End-to-end Topic-Conditioned Natural Language Generation over emergent topics in unlabeled document collections.
Discussing the applications of AI and NLP in the fields of literature and digital humanities.
Generating letters with a neural language model in the style of Italo Svevo, a famous italian writer of the 20th century.