unclear: mid-phrase word in mixed 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. 15 of Qwen3-0.6B. Its strongest snippets are fairly consistent: several of them 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 a word in the middle of a phrase, and the words it picks are very different from one another, so no single theme stands out. It goes quiet or negative on digits and codes inside addresses and product numbers. Turning it up made the model's text drift toward a repeated theme, which does not clearly tie back to the neuron.
Written by Claude from this neuron's activations and steering outputs. Confidence: low. 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.
-
G sites can differ from cell to cell as different nucleic acid sequences are used to create
-
-12 structures for a end of the year 2010 total of around a half
-
45° angle to it. When the sun is lower in the sky, the shadow will be
-
2 years old to the almost uninhabited stretches of prairie in western Kansas. His
-
ClippedText property is set to false⏎and also when passing an area of interest via GetText
-
31-kilometre-long collider; like the Large Hadron Collider, it promises to recreate
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 writing about this thing (this thing I'm writing about it, I'll write it, it's been written about it, it's been written about it, it's been written about it, it's been written about it
Most negative on
Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.
-
provider:|| Postal: Katajanokanlaituri 6B, 00160 Helsinki|⏎Web page: http://www.wider.unu.edu/⏎More information
-
7Availability: In StockCBD Stock No: WW265132<|endoftext|>Ophthalmologists work in hospitals and clinics on land and aboard ships.⏎
-
Drive, Headington, Oxford, OX3 8QQ⏎Back to previous page<|endoftext|>A waterspout is a cyclonic wind event
-
have an idea for an applied, data-centric note of no more than 3,000 words, please send a one-paragraph abstract to email@example.com for consideration.⏎This article discusses how the U.S. Department of Housing and Urban
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
- L7:1302 suppresses
- L12:570 suppresses
- L14:1140 excites
- L4:21 excites
- L14:7 suppresses
- L2:437 suppresses
- L12:2372 weakly excites
- L9:1727 weakly excites
- L10:1631 weakly suppresses
- L1:1260 weakly excites
- L3:856 weakly suppresses
- L0:1 weakly suppresses
- L10:243 weakly excites
- L3:841 weakly excites
- L3:875 weakly excites
- L0:2974 weakly suppresses
- L11:857 weakly excites
- L14:428 weakly suppresses
- L9:31 weakly suppresses
- L12:1687 weakly excites
- L0:236 weakly excites
- L10:1762 weakly suppresses
- L11:1759 weakly excites
- L11:176 weakly excites
Feeds later layers
- L19:779 excites
- L17:622 excites
- L16:1599 suppresses
- L16:1048 suppresses
- L16:1113 excites
- L17:2842 suppresses
- L19:462 suppresses
- L18:2944 suppresses
- L18:1189 excites
- L16:823 excites
- L20:3046 suppresses
- L18:565 excites
- L16:1331 excites
- L17:1199 suppresses
- L18:1678 suppresses
- L18:1308 suppresses opening parenthesis before an acronym
- L16:3012 weakly suppresses
- L18:660 weakly excites
- L18:2461 weakly excites
- L21:129 weakly suppresses
- L18:815 weakly excites
- L16:2621 weakly suppresses
- L16:375 weakly excites
- L17:825 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
- 起
- d
- ourced
- 做一个
- 倍
- OLD
- nyder
- ichier
- 原
- 原始
Suppresses
- (Configuration
- \Configuration
- tery
- quiring
- lescope
- alore
- 蝇
- aleza
- llama
- 但是我