end of document 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. 14 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 the invisible marker that separates one web page from the next. Turning it up mostly made the model ramble or repeat itself, with no clear link to the marker.
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 large step sizes.⏎- Scott E. Fahlman: An Empirical Study of Learning Speed in Back-Propagation Networks, September 1988<|endoftext|>Cardio and weight
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of your hand.⏎Have an amazing project to share? The Electronics Show and Tell is every Wednesday at 7pm ET! To join, head over to YouTube<|endoftext|>Definition of Parabola
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for dark matter in combination with Cold Dark Matter theory and not on its own.⏎This page was last updated June 27, 2015.<|endoftext|>05-11-2009 / Fluvirin –
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Chapter 6 Exercise 6.5, we have discussed the Pythagoras theorem. Other important topics related to the chapter are covered in the following exercises.<|endoftext|>What you will learn in this module⏎Understand different tasks that have to be
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based in part on a lesson by Artis West of North Cobb High School in Kennesaw, Georgia. That lesson plan is included in Featured Lesson Plans.)<|endoftext|>OnabotulinumtoxinA injection is given as a number of tiny
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that it is likely that both of these arguments are correct.”⏎See Johnson’s report at www.mackblackwell.org/web/research/final-reports.htm.<|endoftext|>September 15, 2013 - Tropical Storm Humberto (
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: And so, the second, and the third, and the fourth, and this, and the first, and the second, and, and, and, and, and, and, and, and, and, and, and, and
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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and the sign of the first term.⏎- Have them develop an explicit formula for each sequence.⏎2. A company is offering to pay you one penny on your first day at work and each day after that your salary would triple. Assume you work
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a matrix⏎Find nth maximum⏎Matlab Basics II - Create a vector with a repeated entry⏎Create sequnce 1 4 9 16 25.........⏎Basics: Divide integers to get integer
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Draw PA, PB and PC⏎from P perpendicular to the sides of the triangle where A, B and C⏎are points on the sides. Prove that PA + PB + PC is a constant.⏎Can you decide whether two lines are perpendicular
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learning!⏎- Line up the bowls on an elevated surface (coffee table, ottoman, TV stand). Put one ball in the first bowl, two balls in the second, and so on. Count aloud as you go.⏎- Do a color
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
- L12:1884 strongly excites
- L11:876 excites 'other' after 'among' in lists
- L12:2784 suppresses
- L11:1777 suppresses
- L11:1178 excites
- L13:2412 excites
- L13:2787 suppresses
- L13:1980 suppresses
- L13:996 excites
- L13:2517 suppresses
- L13:1665 excites
- L12:417 excites
- L13:1541 excites
- L13:940 excites
- L12:1603 excites
- L12:763 suppresses
- L13:2294 excites
- L13:1595 suppresses
- L13:2891 excites
- L12:1505 suppresses
- L12:2723 excites
- L13:1389 suppresses
- L12:765 suppresses
- L13:2381 suppresses
Feeds later layers
- L17:2726 strongly suppresses
- L15:2359 suppresses
- L15:457 excites
- L15:60 excites
- L15:2349 excites
- L15:2418 suppresses
- L15:234 excites
- L16:2327 suppresses
- L15:1949 suppresses
- L18:2138 suppresses
- L15:2737 suppresses
- L15:2002 suppresses
- L18:2346 suppresses
- L15:412 suppresses
- L15:1610 suppresses
- L15:1067 suppresses
- L19:2013 suppresses
- L17:1491 suppresses
- L15:137 excites
- L15:132 excites
- L16:1809 suppresses comma inside a list of names or acronyms
- L15:1385 suppresses
- L15:1431 suppresses
- L20:882 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
- esub
- istinguished
- ubs
- >true
- *out
- empo
- reffen
- ious
- Kling
- onic
Suppresses
- 第五
- setVisibility
- 铁
- third
- 第三
- handles
- 第四
- 第七
- scores
- dera