comma after "and" joining clauses
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 lights up on a comma that comes right after "and" or a dash-joined "and" when a new clause starts in ordinary prose. It goes slightly negative on commas inside code parameter lists. Turning it up or down did not produce a clear theme in the replies.
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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the class and helping the class become a successful place of learning.⏎The instructor presented a survey to the students on the first day about the merit of participation; and, how participation can affect the class.⏎The first function of the research plan focuses on
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Hebrides that Columba turned his face when he accepted the terrible penance of Molaise. He bade farewell to his relatives, and, with a few monks who insisted on accompany him whithersoever he might
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band illumination."⏎To get the performance required, however, the team needed to design a massively parallel broadband diffractive neural network for all-optical computation — and, in an example of "set a thief to catch a thief" logic, put
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“capital of the South,” a Jet Age airport promised to put what had once been a minor railroad town within a day’s reach of London and Paris – and, in the minds of some Atlantans, on the same plane of international significance
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measures, meant to treat illnesses caused by under nutrition; and, famishing measures, meant to treat those caused by<|endoftext|>Anorexia may be
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stalled acceptance and implementation of this approach, however, including a high cost of investment, molasses-slow production times, confusion about the most efficient workflows – and, as a result of such concerns, an understandable reluctance on the part of clinicians and
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: "I" (from the person's perspective, not the time). How do you know you are? What is the weather like? What is the weather like? What is the weather like? What is the weather like? What is 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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the other code (too tired 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
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flag... ] 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
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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 of memory⏎Searches within the
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The range() function returns a sequence of numbers starts from a given number to another given number with a given step.⏎It is defined as like below:⏎range(start, stop, step)⏎- start is
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
- L0:2921 weakly suppresses
- L0:499 weakly excites
- L0:792 weakly excites
- L0:154 weakly suppresses
- L0:232 weakly suppresses
- L0:1204 weakly suppresses
- L0:1520 weakly excites
- L0:1 weakly suppresses
- L0:1595 weakly suppresses
- L0:2862 weakly suppresses
- L0:1539 weakly excites
- L0:1207 weakly suppresses
- L0:2223 weakly suppresses
- L0:924 weakly suppresses
- L0:2655 weakly excites
- L0:829 weakly excites
- L0:1498 weakly excites
- L0:575 weakly excites
- L0:427 weakly suppresses
- L0:799 weakly suppresses
- L0:332 weakly suppresses
Feeds later layers
- L2:1881 weakly excites comma right after 'because' or 'that'
- L21:1232 weakly suppresses
- L8:67 weakly excites
- L2:1283 weakly suppresses
- L5:727 weakly suppresses
- L3:908 weakly excites
- L12:604 weakly excites
- L9:204 weakly suppresses
- L6:523 weakly suppresses
- L16:531 weakly excites
- L3:1560 weakly suppresses
- L5:1885 weakly suppresses
- L19:1663 weakly suppresses
- L12:1841 weakly suppresses
- L23:2205 weakly suppresses
- L23:2357 weakly suppresses
- L5:1592 weakly excites
- L2:1116 weakly excites
- L13:1023 weakly suppresses
- L23:431 weakly suppresses
- L17:939 weakly suppresses
- L6:1929 weakly excites
- L14:1141 weakly excites
- L8:1357 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
- PERT
- 𝒃
- DeviceInfo
- 服务能力
- пус
- (Device
- just
- UBE
- устройств
- incess
Suppresses
- orna
- 颜色
- okes
- isposable
- enberg
- ichick
- xic
- clearColor
- etails