Neuron Explorer

Qwen3-0.6B

unclear: word before a count or quantity

A neuron in layer 22 of Qwen3-0.6B. Its strongest snippets are fairly consistent: several of them peak on the same token. It is featured, so it has steering outputs.

What this neuron does

This neuron fires on the word just before a number or amount, such as 'eight' valence electrons or 'two' electrons. It is hard to pin down more precisely. When it was turned down, the model kept coming back to the word 'character'. When it was turned up, the text drifted into unrelated everyday topics.

Written by Claude from this neuron's activations and steering outputs. Confidence: low. 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

    right, contains common non-metals such as chlorine and helium. The noble gases, in the column on the right, almost never react, since they have eight valence electrons, which makes it very stable. The halogens, directly to

  2. #2 peak

    in the elements. This is because the elements are listed in part by their electron configuration. The Alkali metals and Alkaline earth metals have one and two valence electrons (electrons in the outer shell) respectively. These elements lose

  3. #3 peak

    a garden hose.⏎There are only two known coolants compatible with natural uranium. Heavy water – because it contains an isotope of hydrogen that has already absorbed an extra neutron and has no real affinity for absorbing another one – and one of several different

  4. #4 peak

    store their data using sub-atomic particles known as qubits, instead of silicone chips used in traditional machines. Silicon chips store data in binary code – a series of ones and zeros – while qubits represent a range of values simultaneously, which allows

  5. #5 peak

    common causes of syncope are relatively benign, "aborted<|endoftext|>Recall that the conjugate base of an acid is simply the compound formed when an acid loses a hydronium ion (H+).⏎Which the following represent conjugate acid

  6. #6 peak

    - n. - A narrow fissure in rock⏎- n. - A personal or social separation (as between opposing factions)⏎Rifts is worth 8

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 order of a character in a book. How do you get a character to be in the order of the story? One letter, one character, one cirtch, which is a single letter, is a character. How do you

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

    ?⏎1) Hyphens Already Mean Something⏎Hyphens and dashes are actually slightly different, but in practice everybody just uses the same character, ASCII number 45, the hyphen-minus. So let’s just pretend they’re the

  2. #2 peak

    far:⏎Originally Posted by MrFujin⏎Enter a 5-charcter string: hgout⏎String#1: tough ; ASCII code decremented by 32⏎String#2: HGUOT ; reverse order⏎mov char

  3. #3 peak

    are some examples of how an escape could be used.⏎This next example is similar to the first example because the period is also a wild card, which represents any single character. So, if you need match a period and not every character you must

  4. #4 peak

    with a backslash ( `` ). Some common escape sequences are: - `n` Newline - Prints a newline character - `t ` Tab - Prints a tab character - `\ ` Backslash - Prints a backslash ( \ ) - `'

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. L17:2262 strongly suppresses
  2. L9:2350 excites
  3. L10:1170 suppresses
  4. L7:1772 suppresses
  5. L20:1577 suppresses
  6. L7:2276 excites
  7. L10:2107 excites
  8. L7:2605 excites
  9. L9:2240 excites
  10. L4:2762 excites
  11. L21:1642 excites
  12. L16:2848 suppresses
  13. L17:2580 suppresses
  14. L11:619 suppresses
  15. L6:1617 suppresses
  16. L6:13 excites
  17. L20:1269 suppresses
  18. L19:1531 weakly suppresses
  19. L7:2743 weakly excites
  20. L6:1327 weakly excites
  21. L12:1004 weakly excites
  22. L11:2389 weakly suppresses
  23. L21:1593 weakly excites
  24. L12:2224 weakly suppresses

Feeds later layers

  1. L24:1841 suppresses
  2. L27:1623 suppresses
  3. L26:2130 suppresses
  4. L27:1922 suppresses
  5. L25:893 suppresses
  6. L25:2060 suppresses
  7. L23:650 suppresses
  8. L26:2351 suppresses
  9. L27:779 suppresses
  10. L25:2470 suppresses
  11. L25:961 suppresses years and numbers before the digits
  12. L27:1442 weakly suppresses
  13. L23:1994 weakly suppresses
  14. L23:189 weakly suppresses
  15. L23:2081 weakly excites
  16. L24:2091 weakly suppresses
  17. L23:1923 weakly suppresses
  18. L24:2328 weakly suppresses
  19. L27:355 weakly suppresses
  20. L25:771 weakly excites
  21. L25:2738 weakly excites
  22. L23:1451 weakly suppresses
  23. L25:1299 weakly suppresses
  24. L23:395 weakly suppresses

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.

1 values between -32.19 and -31.281 values between -11.22 and -10.312 values between -3.01 and -2.107 values between -2.10 and -1.19339 values between -1.19 and -0.283357 values between -0.28 and 0.63180 values between 0.63 and 1.5513 values between 1.55 and 2.463 values between 2.46 and 3.375 values between 3.37 and 4.28offnegativepositiveoften

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. 口气
  2. ện
  3. IDS
  4. .Tool
  5. IDS
  6. logan
  7. jobId
  8. wage
  9. <Model
  10. nant

Suppresses

  1. character
  2. Character
  3. Character
  4. characters
  5. _character
  6. character
  7. 字符
  8. Characters
  9. _char
  10. char