document boundary separator token
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. 18 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 most strongly on the hidden marker that separates one web page from the next in the training text, right where an abrupt change of topic happens. Its negative side is code and listings. Turning it up or down gave odd, loose text with no clear theme.
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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00<|endoftext|>The reasons and urgency that lead a group of people to just up and leave a
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that<|endoftext|>After splitting genetically from wolves about 135,000 years ago
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requires a bit better understanding of color<|endoftext|>ORLANDO, Florida — The curse of the mummy may truly be fatal
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environmentally incompatible.<|endoftext|>Dhyunsar Mahadev Temple is a major Hindu temple located in the
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needed around planes en route to keep them safely separated.<|endoftext|>FEDERAL Hill House is a squat building in central Providence, within earshot
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rounded to the nearest integer.<|endoftext|>Christine Duncan, MD⏎Sickle cell disease (SCD) affects as
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: the _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
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 *, 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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⏎> 2 if n> 10⏎> 3 print "This might take a while..."⏎> 4 for i = 1 to n⏎> 5 for j = 1 to i⏎> 6 print
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anyway :P)⏎void genFactorial(int x, int t)⏎int total = t; // you probably wouldn't even need total now⏎void main(void) //<|endoftext|>Splattered Plants Should Serve As A Reminder⏎By Phran Novelli
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a sacred religious ceremony, in South Dakota this past summer.⏎Complete information about survivors could not be confirmed<|endoftext|>A simple example of HTML is:⏎<HTML> <HEAD> <TITLE>This is the Title</TITLE> </HEAD> <BODY
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
- L14:67 suppresses
- L15:500 excites
- L6:429 excites
- L17:432 weakly excites
- L16:211 weakly suppresses
- L1:746 weakly excites
- L17:95 weakly suppresses
- L1:79 weakly excites
- L8:2262 weakly suppresses
- L16:180 weakly suppresses
- L6:296 weakly excites
- L9:11 weakly suppresses
- L1:2635 weakly suppresses
- L8:27 weakly excites
- L10:2098 weakly suppresses
- L13:1578 weakly suppresses
- L14:1840 weakly suppresses
- L17:31 weakly suppresses
- L14:57 weakly suppresses
- L2:1250 weakly suppresses
- L10:1124 weakly suppresses
- L2:587 weakly suppresses
- L14:2840 weakly excites
- L15:274 weakly suppresses
Feeds later layers
- L21:441 suppresses
- L20:656 weakly suppresses
- L19:2457 weakly suppresses
- L19:1516 weakly suppresses
- L25:144 weakly excites
- L21:229 weakly suppresses
- L23:205 weakly excites
- L23:1310 weakly excites
- L19:163 weakly suppresses
- L21:367 weakly suppresses
- L20:378 weakly excites
- L23:740 weakly excites 'well' in well-dressed, well-known, well-off
- L25:209 weakly suppresses
- L23:558 weakly excites
- L19:2290 weakly suppresses
- L20:1301 weakly suppresses
- L27:502 weakly suppresses
- L19:1157 weakly suppresses
- L26:145 weakly excites
- L21:282 weakly excites
- L20:1795 weakly suppresses
- L24:2694 weakly suppresses
- L19:2079 weakly suppresses
- L27:256 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
- iskey
- 副校长
- uerdo
- 的道路
- setMax
- congregation
- patible
- aker
- recipient
- 招呼
Suppresses
- olate
- ……
- …)
- …)⏎⏎
- …”
- ,…⏎⏎
- 意思
- ..."); ⏎
- …"
- \")