end of a document
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. 11 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
The neuron is weak and fires at the very end of a piece of text, where the model sees the document-ending marker or a final line break. Turning it up gave unrelated text, so the steering doesn't add much.
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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(6-8) Show all Grade Level⏎Resource Type: Activities⏎Results 1 - 7 of 7 matches⏎From Grid to Home⏎Lisa Gardiner, National Center for Atmospheric Research; Marie
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utes to Heinrich Rudolf Hertz, film critic Francois Truffaut and Charles Dickens, who was born on February 7 1812.<|endoftext|>Combating AIDS Around the Globe⏎Lead story from the February Centerpoint⏎In
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America continental shelf (Fig. 1).⏎Additional publication details⏎Pulley reef: a deep photosynthetic coral reef on the West Florida Shelf, USA<|endoftext|>Good morning lovely people!⏎We’re at the end of another week of home learning
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chance to explore STEM topics in a way that deepens their knowledge while also developing 21st-century skills.⏎Read the rest of this entry »⏎Filed under: Gaming, Services, Software, 3 million dollar grant, Associate Professor,
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input=gadm36_dissolved_nocats output=gadm36_dissolved_cats option=add⏎Figure 3 shows the final categorized layer.<|endoftext|>Despite the good knowledge and practices among the Nepalese migrant women, the breastfeeding
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movies made without consuming any films. It was transferred to six metropolises in the USA via Internet. Toy Story hinted the coming of the era of digital movies<|endoftext|>Short overview of Machine Learning techniques⏎In this article we cover four major types 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: "What is the purpose of the two different types of time, one for the past and one for the future?" This question is about the purpose of the time types, leading to the conclusion that the question is answered by the two time
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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archive.jpr.org.uk/10.1177%2F1359104505053
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two different numbers cant have the same cube). Therefore, by Definition 1, is one-to-one....⏎View Full Document⏎- Spring '09<|endoftext|>part of speech: noun⏎definition 1:
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an-RM⏎Am Ind Hyg Assoc J 1980 Oct; 41(10):758-765⏎The effectiveness of open versus closed-face c
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to get the integral into a reasonable form⏎Doing u-substitution twice (second time with w)⏎⇐ Use this menu to view and help create subtitles for this video in many different languages. You'll probably want to hide YouTube's captions if using
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
- L10:2423 excites
- L10:1932 weakly suppresses
- L10:58 weakly excites
- L10:196 weakly excites
- L10:710 weakly suppresses
- L7:1070 weakly suppresses
- L2:1037 weakly excites
- L7:61 weakly suppresses
- L3:194 weakly suppresses
- L9:2332 weakly suppresses
- L0:2863 weakly excites
- L10:72 weakly excites
- L6:843 weakly excites
- L3:547 weakly suppresses
- L3:329 weakly excites
- L0:876 weakly excites
- L1:1340 weakly suppresses
- L6:2345 weakly excites
- L6:1214 weakly suppresses
- L7:1663 weakly suppresses
- L10:701 weakly suppresses everyday objects and animals, mid-word
- L7:63 weakly excites
- L2:542 weakly suppresses
- L2:1919 weakly excites
Feeds later layers
- L13:969 excites
- L12:2138 excites
- L15:2544 excites
- L16:2510 excites
- L12:326 suppresses
- L15:2249 suppresses
- L12:1900 weakly suppresses end of document boundaries
- L14:571 weakly excites
- L14:2525 weakly excites
- L12:1439 weakly excites
- L12:849 weakly excites
- L16:1251 weakly suppresses
- L17:1980 weakly suppresses
- L15:1088 weakly excites
- L22:163 weakly excites
- L23:1891 weakly excites
- L12:1199 weakly suppresses
- L16:2814 weakly excites
- L22:1685 weakly suppresses
- L12:1964 weakly excites
- L13:595 weakly excites
- L13:1624 weakly suppresses
- L12:1690 weakly suppresses
- L15:101 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
- afford
- ease
- fl
- nil
- heit
- 跤
- arith
- ifndef
- NSS
- nia
Suppresses
- obody
- 另一个
- ーター
- 了他的
- 观光
- _mirror
- _solution
- ivor
- 绲
- ți