end of text token after prose
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. 12 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 responds strongly to the hidden marker that ends a document, especially when the text just before it is a finished sentence. Turning it up did not produce a clear theme in the written output.
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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environmental variables, or logging properties⏎- Monitor Spark using the web UIs, metrics, and external instrumentation⏎- Understand performance tuning considerations⏎- This course is<|endoftext|>Class 1M have been learning the story of Snow White and the Seven D
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will discuss a basic MySQL installation on a Linux virtual server, and some of the basic MySQL commands.⏎Full documentation can be found on the MySQL.com website here.<|endoftext|>The law applicable to military strategic use of outer space⏎New technologies and the law
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engine optimization (SEO) efforts by generating optimized content for your site. Additionally, AI can help you identify and prevent potential blog problems before they become big issues.<|endoftext|>Turbine oils are subjected to a wide range of conditions -
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the area was not opened for shellfish harvesting, whereas in 2000, the number of days during which the area was opened ranged from 6<|endoftext|>The picture from Ani's tomb shows a full procession with
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reversed, thereby ensuring that the anode surface always remains clean. If the switching frequency is high enough, dual-magnetron sputtering can also eliminate ar<|endoftext|>Mexican War Of Independence And Early Republic 1810-50
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of the photos. Moreover, this approach not only makes it possible to represent the citizens’ natural behavior, which may change as they see themselves in front of the<|endoftext|>Stand up for the facts!⏎Our only agenda is to publish the truth so you
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: that the position of principal,____________,______________,____________________________________________________________________________________________________________','Resultiard','pol','__
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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ography, July 2, 2014. DOI: 10.1007/s13524-014-0308-7<|endoftext|>Designs and simulation results are given for two
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Edition)⏎|Author||Michael P. O'Donnell, Margo Wood|⏎|Number Of Pages||408|⏎Write a review⏎Note: HTML is not translated!⏎Rating: Bad Good⏎Enter the code in the box below
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continues]⏎Cite This Essay⏎(2012, 05). The Struggle for Power in the Ussr. StudyMode.com. Retrieved 05, 2012, from http://www.st
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quote exceptions. Similarly, wrap the string in single quotes instead of double quotes if you want to print double quotes in a string:⏎print(‘John says “Hello there!”’)⏎John says “Hello there!”⏎## Use escape sequences 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
- L9:263 suppresses
- L10:58 excites
- L9:1573 suppresses
- L11:1785 suppresses
- L7:885 excites
- L10:80 excites
- L10:553 suppresses list-style essay phrasing, weak
- L10:1144 suppresses sentence openers after a break
- L4:121 excites
- L10:689 excites
- L10:510 excites
- L3:187 weakly excites
- L10:507 weakly suppresses
- L10:196 weakly suppresses
- L8:663 weakly suppresses
- L11:2225 weakly excites
- L9:23 weakly suppresses
- L3:157 weakly excites
- L3:17 weakly suppresses
- L10:1042 weakly excites
- L4:50 weakly excites
- L9:949 weakly excites
- L4:2400 weakly suppresses
- L8:2725 weakly excites line-break tokens inside wrapped text
Feeds later layers
- L19:1466 excites
- L18:1518 excites
- L16:926 suppresses
- L16:913 suppresses
- L15:910 excites
- L17:261 suppresses
- L15:605 suppresses
- L18:1633 excites
- L14:2251 excites
- L13:2695 excites
- L18:722 excites
- L14:1811 excites word before an evaluative adjective in essays
- L16:1891 excites
- L17:1554 weakly excites
- L16:1543 weakly suppresses
- L17:1933 weakly excites
- L15:2706 weakly excites
- L13:129 weakly excites
- L17:94 weakly excites
- L19:59 weakly excites
- L15:1727 weakly excites
- L27:2352 weakly suppresses
- L20:312 weakly suppresses
- L21:96 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
- 网小编
- ]*
- .getRuntime
- <$
- [*
- <|endoftext|>
- *$
- wright
- * ⏎
- AdapterManager
Suppresses
- ivism
- vib
- 🏻
- 这支
- 样板
- akin
- 🏽
- idity
- 点了
- elled