Neuron Explorer

Qwen3-0.6B

end-of-document token between unrelated texts

A neuron in layer 19 of Qwen3-0.6B. Its strongest snippets are very consistent: they mostly peak on the same token. It is featured, so it has steering outputs.

What this neuron does

This neuron mostly switches on at the hidden marker that separates one web page or document from an unrelated one. Its strongest reactions are small, and its rare strong negative reactions come from programming and language-name contexts, so it is hard to read as one clear idea.

Written by Claude from this neuron's activations and steering outputs. Confidence: medium. Think it is wrong? Flag it (opens a prefilled issue on GitHub).

Fires most on

The text windows where this neuron's activation was highest. Amber marks positive activation; the outlined token is the peak. Hover a token for its strength.

  1. #1 peak

    contract when it expires.⏎In the next part, we will create the simple method that creates the options contract ticker that identifies the contract in the options chain.<|endoftext|>Rayner, Hugh, Thomas, Mark, Milford, David⏎This text

  2. #2 peak

    time.⏎You should give examples from dynamic typed languages instead, e.g. clojure.⏎Here's one example:<|endoftext|>The commerce of the ancient world was gathered into the warehouses of Tyre. "

  3. #3 peak

    ressor framework will help guide management of stream fishes, and provide a better understanding of the mechanisms underlying responses of different species.<|endoftext|>The Liber Pontificalis is a book of information on th early popes

  4. #4 peak

    can include things like making sure there are enough pencils and<|endoftext|>FDA carries out asbestos tests in cosmetic talc after concerns are raised⏎“From

  5. #5 peak

    Keeping common surfaces clean, and⏎- Staying home when you are sick.⏎Currently there are no advisories restricting travel to the Arabian Peninsula or South Korea.<|endoftext|>"The most significant fact is that it will not fall from inside pressure. Only outside

  6. #6 peak

    . Here's a class called CarParts that declares a static inner class called Wheel. If we consider the real-world, we can find many objects around us,<|endoftext|>18th Jan 12 14:01<< Go back

Steering

Push this neuron up or down while the model writes, and watch what changes. The outputs were generated ahead of time, so nothing runs in your browser.

turned down a lot
Prompt

Here is something I have been thinking about lately: the first and the last term in a given vector mutates to their mutative mutane mutane mutane mutane mutane mutane mutane mutane mutane mutane mutane mutane mutane mutane mutane mutane

Most negative on

Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.

  1. #1 peak

    has been proved to be a useful and expressive tool in various modern languages. In particular, many aspects of this PEP were inspired by how pattern matching works in Rust and Scala .⏎Both those languages are statically typed, which allows the compiler to

  2. #2 peak

    Marija Gimbutas, Mary, matriarchy, mythology, Robert Graves, symbols⏎In Fil

  3. #3 peak

    products. In the spring of 1934, the Franks r…⏎E-pasta adrese, uz kuru nosūtīt darba saiti:⏎Saite uz darbu:<|endoftext|>Branch of

  4. #4 peak

    But on-the-dock inspections are just a small part of how an agency like the FDA works to protect the nation's food sources, said Joe Raulinaitis, a spokesman in the agency's New England District office.⏎"It's an

Connections

Show on map

Which neurons in earlier layers feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.

Fed by earlier layers

  1. L8:378 strongly suppresses
  2. L14:2645 suppresses
  3. L3:2424 suppresses
  4. L4:794 suppresses
  5. L1:1825 suppresses
  6. L17:1159 suppresses
  7. L6:696 excites
  8. L18:1956 suppresses
  9. L4:2877 excites
  10. L18:1203 excites end of document marker
  11. L10:112 weakly suppresses
  12. L9:1489 weakly excites
  13. L18:1444 weakly excites
  14. L17:1634 weakly suppresses
  15. L9:214 weakly excites
  16. L17:1006 weakly suppresses
  17. L1:1877 weakly suppresses
  18. L17:1074 weakly excites
  19. L16:1509 weakly excites
  20. L18:569 weakly excites
  21. L17:343 weakly excites
  22. L18:491 weakly suppresses
  23. L16:604 weakly suppresses
  24. L8:16 weakly suppresses

Feeds later layers

  1. L23:2680 strongly suppresses
  2. L24:1090 suppresses
  3. L21:2204 suppresses
  4. L23:2258 suppresses
  5. L21:521 excites
  6. L24:2041 suppresses
  7. L22:2396 suppresses
  8. L23:1665 suppresses
  9. L24:2636 suppresses
  10. L21:1667 suppresses
  11. L22:1168 suppresses
  12. L20:2663 excites
  13. L23:2276 suppresses
  14. L22:2524 suppresses
  15. L24:1705 suppresses
  16. L20:1402 excites
  17. L21:722 excites
  18. L21:2593 suppresses unclear: fractions and odd characters mid-word
  19. L23:1809 weakly excites
  20. L27:2573 weakly suppresses
  21. L22:2181 weakly excites
  22. L22:2404 weakly excites
  23. L22:870 weakly suppresses
  24. L21:1317 weakly excites 'in' in 'this, in turn' phrases

Activation histogram

How often this neuron fires at each strength. Almost always it does close to nothing (the tall bars in the middle); the snippets above are the rare moments it fired hard, amber for positive and blue for negative.

2 values between -0.70 and -0.633 values between -0.26 and -0.205 values between -0.20 and -0.149 values between -0.14 and -0.0839 values between -0.08 and -0.021394 values between -0.02 and 0.04963 values between 0.04 and 0.11497 values between 0.11 and 0.17288 values between 0.17 and 0.23211 values between 0.23 and 0.29125 values between 0.29 and 0.3594 values between 0.35 and 0.4173 values between 0.41 and 0.4853 values between 0.48 and 0.5441 values between 0.54 and 0.6032 values between 0.60 and 0.6622 values between 0.66 and 0.7219 values between 0.72 and 0.7813 values between 0.78 and 0.854 values between 0.85 and 0.912 values between 0.91 and 0.973 values between 0.97 and 1.033 values between 1.03 and 1.094 values between 1.09 and 1.154 values between 1.28 and 1.342 values between 1.34 and 1.401 values between 1.40 and 1.462 values between 1.71 and 1.77offnegativepositiveoften

Logit lens

The words this neuron nudges the model toward (amber) or away from (blue) when it fires. A hint, not a label: many neurons work through later layers instead.

Promotes

  1. 另一边
  2. atever
  3. ¯¯¯¯
  4. ¯¯
  5. .arraycopy
  6. 때문이다
  7. nonetheless
  8. 偏偏
  9. [array
  10. 是韩国

Suppresses

  1. mut
  2. mut
  3. (mut
  4. _mut
  5. Mut
  6. mute
  7. Mut
  8. crate
  9. mutations
  10. (Some