equals sign in code assignments
A neuronOne of thousands of tiny dials inside each layer. It reads the text so far and produces a number, its activation, that nudges what the model writes next. in layerOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. 1 of Qwen3-0.6B. Its strongest snippets are very consistent: they mostly peak on the same token. It is featuredA neuron picked for the full treatment: steering outputs and a written explanation. About 3,000 of the 86,000 neurons are 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 activationThe number a neuron produces for a token. Large positive means it fired hard; negative means it pushed the other way. was highest. Amber marks positive activation; the outlined tokenA piece of text the model reads at once: often a word, sometimes part of a word or a punctuation mark. is the peak. Hover a token for its strength.
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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)
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⏎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
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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 =
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be partially applied and passed around to higher order functions, like so:⏎ghci> :m + Data.Bool.Extras⏎ghci> let yesOrNo = bool
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*, int, size_t );⏎instead of the two overloaded versions provided in C++.⏎/* memchr example */⏎int main ()⏎char * pch;⏎char str = "Example string";⏎pch = (char
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.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
SteeringAdding a push along a neuron while the model writes, to see how its output changes. Turning it up or down.
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.
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.
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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
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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
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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
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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 mapWhich neuronsOne of thousands of tiny dials inside each layer. It reads the text so far and produces a number, its activation, that nudges what the model writes next. in earlier layersOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.
Fed by earlier layers
- L0:1224 suppresses
- L0:178 suppresses
- L0:1301 suppresses
- L0:300 weakly excites
- L0:732 weakly excites
- L0:1022 weakly suppresses "of" in fixed phrases like plain of
- L0:2576 weakly excites
- L0:1875 weakly excites
- L0:799 weakly suppresses
- L0:1062 weakly excites
- L0:1463 weakly suppresses
- L0:13 weakly excites
- L0:749 weakly suppresses
- L0:2730 weakly suppresses
- L0:488 weakly excites
- L0:1414 weakly excites
- L0:351 weakly suppresses
- L0:761 weakly suppresses
- L0:1025 weakly excites
- L0:2361 weakly suppresses
- L0:2376 weakly excites
- L0:1031 weakly suppresses
- L0:1117 weakly suppresses
- L0:1897 weakly excites
Feeds later layers
- L3:1575 weakly suppresses
- L17:1991 weakly suppresses
- L10:2239 weakly suppresses
- L10:83 weakly suppresses
- L21:824 weakly suppresses
- L6:15 weakly excites
- L4:3058 weakly excites
- L5:1843 weakly suppresses
- L2:1561 weakly excites
- L18:2534 weakly suppresses
- L14:1217 weakly excites
- L17:1171 weakly suppresses
- L16:927 weakly suppresses
- L17:1156 weakly suppresses
- L11:2299 weakly suppresses
- L7:2970 weakly excites
- L2:2498 weakly suppresses
- L10:1375 weakly excites
- L23:933 weakly suppresses
- L9:2756 weakly suppresses
- L13:1616 weakly suppresses
- L22:998 weakly suppresses
- L14:119 weakly excites
- L3:1463 weakly excites
Activation histogramA chart of how often a neuron takes each activation value.
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.
Logit lensReading which output tokens a neuron pushes toward or away from, straight off its output weights, before the later layers have their say.
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 layersOne step in the stack the text passes through. Qwen3-0.6B has 28 layers, each with 3,072 neurons. instead.
Promotes
- purposes
- Pictures
- arlo
- .ResponseWriter
- bos
- intention
- consum
- os
- य
- fos
Suppresses
- agged
- êm
- ;]/
- ugged
- tlement
- íg
- ọc
- -tra
- ⌠
- 阮