News for hackers. Stuff that matters.

lakshith-403

Thank you
Interesting. I think OpenAI here uses sparse autoencoders to map out sparse activation patterns in networks. Comparing them to how a real person reasons about a situations.

Inspectus, on the other hand is a general tool to visualize how transformer models pay attention to different parts of the data they process.

I'm not a primary user. Just cleaned up the existing codebase to make it open source. But you could use this to visualise attentions and debug the model.

For an example if you're working on a Q&A model, you can check which tokens in the prompt contributed to the output. It's possible to detect issues like output not paying attention to any important part of the prompt.

Show HN: We've open-sourced our LLM attention visualization library

https://github.com/labmlai/inspectus

Inspectus allows you to create interactive visualizations of attention matrices with just a few lines of Python code. It’s designed to run smoothly in Jupyter notebooks through an easy-to-use Python API. Inspectus provides multiple views to help you understand language model behaviors. If you have any questions, feel free to ask!

( Read More... | 15 comments | on HN )