first token of a text
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. 0 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 fires on the very first token of a piece of text when that token is a line break. It does not respond to the meaning of the words, only to the start of a document. Steering with it gave unrelated text.
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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⏎1. n. Any one of numerous species of marine gastropods belonging to
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⏎- SOA services have self-describing interfaces in platform-independent XML documents. Web
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⏎Lin CC, Lin XM, Zou Y, Zhang L (200
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⏎Some people use their fridge to store everything in their kitchen. Your fridge is not
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⏎know much about it beyond that and couldn't find much information about⏎it on
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⏎First of all, let us know what is Gandhi Jayanti? We can proudly
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 have been thinking about lately. I have been thinking about lately. I have been thinking about lately. I have been thinking about lately. I have been thinking about now. I have been thinking about now. I have been thinking about now
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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<|endoftext|>House in Space, from a NASA Remix Challenge. Credit: Cookieater20
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<|endoftext|>10 Tips for Parents of Prospective College Students⏎1. Choosing a Career
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<|endoftext|>Active transportation refers to non-motorized transportation modes, such as bicycling and
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<|endoftext|>Public holidays in Pakistan are different than bank holidays in the country. While all of
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
None: this is the first layer.
Feeds later layers
- L1:816 strongly excites
- L1:883 suppresses
- L2:855 suppresses
- L2:469 excites
- L1:2679 excites
- L4:658 suppresses
- L1:1143 suppresses
- L2:674 excites
- L2:1306 excites
- L3:781 suppresses
- L6:2030 suppresses
- L6:1126 weakly excites
- L16:313 weakly suppresses
- L3:70 weakly excites
- L27:454 weakly excites
- L1:1526 weakly suppresses
- L21:264 weakly suppresses
- L21:625 weakly excites
- L20:1081 weakly suppresses
- L20:1085 weakly excites
- L17:1582 weakly suppresses
- L17:1311 weakly suppresses
- L6:2021 weakly excites
- L7:1447 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
- voy
- sterdam
- าย
- taire
- osite
- ponsive
- onError
- 탈
- atic
- ят
Suppresses
- 仍将
- $body
- pra
- 胎
- 风吹
- thor
- timing
- ⇌
- wheat
- LCS