Neuron Explorer

Qwen3-0.6B

equals sign in code assignments

A neuron in layer 1 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 fires on the equals sign in code, such as 'int total = ...' or 'char str[] = ...', where a variable is being set. The writing it produced when turned up was ordinary prose, so the code link is only visible in the examples.

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

    to check who it was that posted it, and I can't see just now anyway :P)⏎void genFactorial(int x, int t)⏎int total = t; // you probably wouldn't even need total now⏎void main(void)

  2. #2 peak

    ⏎But here thing is, save() method can return that primary key id value which is generated by hibernate and we can see it by⏎long s = session.save(k);⏎In this same case, persist() will never give any value

  3. #3 peak

    necessary to know it,⏎but in some cases the difference between shared and separated objects yields different orders of space or time complexity.⏎Consider the infinite list⏎let x =

  4. #4 peak

    be partially applied and passed around to higher order functions, like so:⏎ghci> :m + Data.Bool.Extras⏎ghci> let yesOrNo = bool

  5. #5 peak

    *, int, size_t );⏎instead of the two overloaded versions provided in C++.⏎/* memchr example */⏎int main ()⏎char * pch;⏎char str = "Example string";⏎pch = (char

  6. #6 peak

    .DataSource, DataSet) ' Get the DataTableCollection. Dim tablesCollection As DataTableCollection = thisDataSet.Tables ' Get a specific table by name. Dim table As DataTable = tablesCollection("Suppliers") Console.WriteLine(table.TableName) End Sub⏎Available since

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: how can I get the best of the best of the best of the best of the best of the best of the best of the best of the best of the best of the best of the best of the best of the best of the best

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

    void * memchr ( const void * ptr, int value, size_t num );⏎void * memchr ( void * ptr, int value, size_t num );⏎Locate character in block of memory⏎Searches within the first num bytes of

  2. #2 peak

    the value is not found, the function returns a null pointer.⏎In C, this function is only declared as:⏎void * memchr ( const void *, int, size_t );⏎instead of the two overloaded versions provided in C++.⏎/* mem

  3. #3 peak

    file... -lm [ library... ] #include <math.h> double ldexp(double x, int exp);⏎float ldexpf(float x, int exp);⏎long double ldexpl(long double x, int exp);⏎These functions computes the quantity

  4. #4 peak

    compiler:⏎As humans though, the above is a lot more like gibberish.⏎void * load_model_from_disk(const char *);⏎void draw_model(void *, float, float, float);⏎void deallocate_model(void *);⏎And that is why I am

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. L0:1224 suppresses
  2. L0:178 suppresses
  3. L0:1301 suppresses
  4. L0:300 weakly excites
  5. L0:732 weakly excites
  6. L0:1022 weakly suppresses "of" in fixed phrases like plain of
  7. L0:2576 weakly excites
  8. L0:1875 weakly excites
  9. L0:799 weakly suppresses
  10. L0:1062 weakly excites
  11. L0:1463 weakly suppresses
  12. L0:13 weakly excites
  13. L0:749 weakly suppresses
  14. L0:2730 weakly suppresses
  15. L0:488 weakly excites
  16. L0:1414 weakly excites
  17. L0:351 weakly suppresses
  18. L0:761 weakly suppresses
  19. L0:1025 weakly excites
  20. L0:2361 weakly suppresses
  21. L0:2376 weakly excites
  22. L0:1031 weakly suppresses
  23. L0:1117 weakly suppresses
  24. L0:1897 weakly excites

Feeds later layers

  1. L3:1575 weakly suppresses
  2. L17:1991 weakly suppresses
  3. L10:2239 weakly suppresses
  4. L10:83 weakly suppresses
  5. L21:824 weakly suppresses
  6. L6:15 weakly excites
  7. L4:3058 weakly excites
  8. L5:1843 weakly suppresses
  9. L2:1561 weakly excites
  10. L18:2534 weakly suppresses
  11. L14:1217 weakly excites
  12. L17:1171 weakly suppresses
  13. L16:927 weakly suppresses
  14. L17:1156 weakly suppresses
  15. L11:2299 weakly suppresses
  16. L7:2970 weakly excites
  17. L2:2498 weakly suppresses
  18. L10:1375 weakly excites
  19. L23:933 weakly suppresses
  20. L9:2756 weakly suppresses
  21. L13:1616 weakly suppresses
  22. L22:998 weakly suppresses
  23. L14:119 weakly excites
  24. L3:1463 weakly excites

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 -0.40 and -0.382 values between -0.37 and -0.353 values between -0.35 and -0.331 values between -0.31 and -0.292 values between -0.29 and -0.274 values between -0.27 and -0.264 values between -0.26 and -0.245 values between -0.24 and -0.227 values between -0.22 and -0.209 values between -0.20 and -0.1818 values between -0.18 and -0.1726 values between -0.17 and -0.1526 values between -0.15 and -0.1344 values between -0.13 and -0.1172 values between -0.11 and -0.09118 values between -0.09 and -0.07157 values between -0.07 and -0.06237 values between -0.06 and -0.04388 values between -0.04 and -0.02663 values between -0.02 and -0.00711 values between -0.00 and 0.02479 values between 0.02 and 0.04316 values between 0.04 and 0.05205 values between 0.05 and 0.07128 values between 0.07 and 0.0989 values between 0.09 and 0.1179 values between 0.11 and 0.1339 values between 0.13 and 0.1535 values between 0.15 and 0.1620 values between 0.16 and 0.188 values between 0.18 and 0.204 values between 0.20 and 0.223 values between 0.22 and 0.241 values between 0.24 and 0.251 values between 0.25 and 0.271 values between 0.27 and 0.291 values between 0.31 and 0.33offnegativepositiveoften

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. purposes
  2. Pictures
  3. arlo
  4. .ResponseWriter
  5. bos
  6. intention
  7. consum
  8. os
  9. य
  10. fos

Suppresses

  1. agged
  2. êm
  3. ;]/
  4. ugged
  5. tlement
  6. íg
  7. ọc
  8. -tra
  9. ⌠
  10. 阮