This is a post to officially announce the sae-vis library, which was designed to create feature dashboards like those from Anthropic’s research.
Summary
There are 2 types of visualisations supported by this library: feature-centric and prompt-centric.
The feature-centric vis is the standard from Anthropic’s post, it looks like the image below. There’s an option to navigate through different features via a dropdown in the top left.
The prompt-centric vis is centred on a single user-supplied prompt, rather than a single feature. It will show you the list of features which score highest on that prompt, according to a variety of different metrics. It looks like the image below. There’s an option to navigate through different possible metrics and choices of token in your prompt via a dropdown in the top left.
You might also be interested in reading about Neuronpedia, who make use of this library in their visualizations.
If you’re interested in getting involved, please reach out to me or Joseph Bloom! We will also be publishing a post tomorrow, discussing some of the features we’ve discovered during our research.
SAE-VIS: Announcement Post
This is a post to officially announce the sae-vis library, which was designed to create feature dashboards like those from Anthropic’s research.
Summary
There are 2 types of visualisations supported by this library: feature-centric and prompt-centric.
The feature-centric vis is the standard from Anthropic’s post, it looks like the image below. There’s an option to navigate through different features via a dropdown in the top left.
The prompt-centric vis is centred on a single user-supplied prompt, rather than a single feature. It will show you the list of features which score highest on that prompt, according to a variety of different metrics. It looks like the image below. There’s an option to navigate through different possible metrics and choices of token in your prompt via a dropdown in the top left.
Other links
Here are some more useful links:
GitHub repo
User Guide—Google Doc explaining how to use the library
Dev Guide—Google Doc explaining more about how the library was built, for if you’d like to try and extend it / build off it
Demo Colab—includes examples, with code explained
You might also be interested in reading about Neuronpedia, who make use of this library in their visualizations.
If you’re interested in getting involved, please reach out to me or Joseph Bloom! We will also be publishing a post tomorrow, discussing some of the features we’ve discovered during our research.