thanks! we asked the model to generate some synonyms and antonyms (in this case, we have "cold" and "impassive" vs "affectionate" and "sensitive")
Then, we ask the model to behave that way (with a prompt), and store the difference in activations for each pair. Then, a PCA can be used to extract the principal component, giving use the steering vector. We do most of this using the repeng library, and the author goes into a bit more detail on how it's done on her [blog](https://vgel.me/posts/representation-engineering/#How_do_we_...?)
