the word 'name' in definitions
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. 16 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 fires on the word 'name' when it is being used to say what something is called, such as 'the name given to', 'her name', or 'function name'. Turning it up made the model keep talking about names and titles, so the link is clear.
Written by Claude from this neuron's activations and steering outputs. Confidence: high. 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 part of the telephone book that lists residential and business telephone numbers in alphabetical order by name, usually without any advertising copy⏎- White Pages are the name given to one of the three main components of UDDI, the protocol used
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on a book shelf, and larger, white, adult-sized calf lying beside a beat-up MacBook Pro.⏎Ginger Coons, a PhD student who prefers her name rendered as “ginger
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used in defining function is:⏎- Return type. This is the type of value that is returned by the function and can be a type C data.⏎- Function name. This is the identifier in which you can use to call your function.⏎-
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new means for preventing such, and it’s a lot more friendly to the environment and company budgets.⏎That’s right, Siftek. It’s the new name in natural gas dehydration. At least, its creators are hoping it will be.
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Linnaeus, Euphorbia caput-medusae. It was brought to the Netherlands between the 1700s.⏎The plant’s name, Medusa head, refers to how the crowns of its white and yellow
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motivates me to hear more stories from people who are often called nones, people who do not claim a religion. I actually don’t care much for the name nones because it assumes that people without a religious tradition are missing something. Some
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 in the "best of the point to point to point to point to point to point to point to point to point to point to point to point to point to point to point to point to point to point to point to point to point
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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" >>> >>> len(s) 13 >>> >>> len("") 0 >>>⏎>>> >>> s3 = '' # empty string using single quotes >>> s3 '' >>> >>> s4 = "" # empty string using double quotes >>> s4 ''
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the text on this page. Any software described in this text has its own copyright notice and license, which can usually be found in the distribution itself.<|endoftext|>Disin
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God and the Holy<|endoftext|>Previous: [SVG] How to draw a rectangle?⏎<svg height="210" width="500"> <polygon points="200,10 250,190
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stars and 13 red and white stripes to represent the original 13 colonies that broke from British rule. The stars were arranged on a blue background to represent a "new constellation." In 1795, two more stars and
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
- L15:2621 excites
- L5:944 suppresses
- L15:1559 suppresses
- L12:1772 suppresses
- L8:1224 excites
- L14:3052 excites
- L10:1001 suppresses
- L15:2973 suppresses
- L9:1040 excites
- L11:2030 suppresses
- L11:2991 excites
- L12:1708 excites
- L10:2243 suppresses
- L15:2595 suppresses
- L10:809 suppresses
- L12:2197 excites
- L6:1650 suppresses
- L2:2118 suppresses
- L10:741 suppresses
- L15:856 excites
- L11:1769 weakly suppresses
- L8:2148 weakly excites
- L7:1348 weakly suppresses
- L3:2267 weakly excites
Feeds later layers
- L26:1323 excites
- L25:635 excites
- L19:1913 excites
- L22:1507 excites
- L23:1793 excites
- L18:2981 excites
- L20:766 excites
- L17:2480 excites
- L22:1311 excites
- L22:1976 excites
- L24:1138 excites
- L17:2186 excites
- L21:2820 excites
- L20:1740 excites
- L17:1271 excites
- L27:820 excites
- L17:1040 suppresses
- L17:2498 excites
- L23:626 excites
- L19:1378 excites
- L20:1462 excites
- L21:2555 weakly excites
- L25:2775 weakly suppresses
- L20:1898 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
- 名字
- 名称
- name
- name
- 姓名
- 称呼
- names
- 命名
- 这个名字
- 的名字
Suppresses
- egral
- ढ
- /GPL
- aat
- arious
- lage
- яд
- 醌
- 与发展
- SourceType