end-of-text boundary tokens
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. 26 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 invisible marker the model uses to show that one document has ended and another begins. Turning it up made the model fall into repeating the word 'either', and turning it down gave repetitive talk about plots.
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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locate.<|endoftext|>Science Fair Project Encyclopedia⏎The World Factbook⏎The World Factbook is an
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Project:<|endoftext|>After years of experience and "combing through" catalogs⏎to find the best
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that<|endoftext|>After splitting genetically from wolves about 135,000 years ago
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data from TC1.<|endoftext|>The concept of welfare state⏎We all know that most of the modern democratic countries
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to like.<|endoftext|>The late Dominica-born writer Jean Rhys, best known for her novel “
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-Pecos.<|endoftext|>top of page⏎Patterns of tree-liana interactions: distribution and host preference of
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: theorems in geometric plots which plot theorems in plot plots. plot plots plots plots plots plot plots plots plots plots plots plot plots plots plots plots plot plots plots plots plots plot plots plots plots plots plot plots plots plots plots plot plots
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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conuts and banana leaves<|endoftext|>const void * memchr ( const void * ptr, int value, size_t num );⏎void * memchr ( void * ptr, int value, size_t num );⏎Locate character in block
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from some neighborhoods and into others.⏎1. A storage unit designed to hold various objects.⏎2. To cause a structure to shift so that it is out of plumb.⏎1. A force that causes a structure to shift so that it is
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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) //<|endoftext|>
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x80;⏎P0 = 0x98;⏎P0 = 0xC0;⏎P0 = 0xff;⏎} while(1); // Endless loop<|endoftext|>Wisconsin Well Water: Planning Web-Based⏎Resources to
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
- L21:341 strongly suppresses
- L22:259 suppresses
- L25:2557 suppresses
- L25:393 suppresses unclear: end-of-document markers
- L20:508 excites
- L20:85 suppresses
- L25:500 excites
- L21:328 excites
- L20:843 excites
- L13:643 suppresses
- L25:1813 excites
- L25:1373 excites
- L19:542 suppresses
- L15:574 suppresses
- L9:214 excites
- L16:496 excites
- L20:96 suppresses
- L14:67 suppresses
- L21:155 weakly suppresses
- L19:415 weakly suppresses
- L18:109 weakly suppresses
- L2:30 weakly suppresses
- L0:958 weakly suppresses
- L2:1287 weakly suppresses
Feeds later layers
- L27:619 strongly excites
- L27:1341 excites
- L27:274 excites document boundary, code keywords next
- L27:1666 weakly excites
- L27:2341 weakly excites
- L27:1063 weakly excites
- L27:614 weakly suppresses
- L27:1872 weakly excites
- L27:2654 weakly excites
- L27:842 weakly excites
- L27:2159 weakly suppresses
- L27:1779 weakly excites
- L27:1220 weakly excites
- L27:2553 weakly suppresses capital T starting a word
- L27:3023 weakly suppresses
- L27:1370 weakly excites
- L27:1899 weakly excites
- L27:1723 weakly excites
- L27:1419 weakly suppresses
- L27:1873 weakly excites
- L27:2660 weakly suppresses
- L27:1521 weakly excites
- L27:3055 weakly suppresses lowercase 'l' starting a word
- L27:1146 weakly suppresses
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
- //
- //
- //⏎
- //⏎
- )//
- //"
- /**
- // ⏎
- /*
- /*
Suppresses
- ilight
- ше
- ande
- ored
- unist
- abled
- epid
- isol
- obao
- irmed