Nice work! I was wondering what context length you were using when you extracted the LLM activations to train the SAE. I could not find it in the paper but I might also have missed it. I know that OpenAI used a context length of 64 tokens in all their experiments which is probably not sufficient to elicit many interesting features. Do you use a variable context length or also a fixed value?
Nice work! I was wondering what context length you were using when you extracted the LLM activations to train the SAE. I could not find it in the paper but I might also have missed it. I know that OpenAI used a context length of 64 tokens in all their experiments which is probably not sufficient to elicit many interesting features. Do you use a variable context length or also a fixed value?
We use 1024, though often article snippets are shorter than that so they are separated by BOS.