"to" after 'for X' infinitives
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. 4 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
Fires on the word "to" in phrases like "For it to work" or "for evolution to be true," where a "for someone or something" phrase introduces an action. Its strongest negative cases are the word fragment "bs" and "owns" in place names like suburbs. Turning it up gave text with no clear shared theme.
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.
-
another device.⏎For it to work, at least two devices need to be Sparsh-enabled. A user wanting
-
ippedTextTolerance property allows you to⏎define a rectangular area in the center of the character, the⏎entire of which must be visible for the character to be visible.⏎The width and height of the rectangular area are determined by the⏎
-
new antibiotic.⏎For treatment to be effective and practical, it must be simple to administer by mouth as a single
-
and photographic lineups. Lineups involve showing the witness a group of possible suspects. Photographic lineups provide a selection of pictures of possible suspects for the witness to choose from. Showups are done by showing one suspect to the witness.⏎The
-
to carbon dating, kids of faith have questions these days. They're struggling to put together what their schools teach about science and what their beliefs are.⏎For evolution to be true, the earth must be billions of years old, with life-forms
-
being punishable by the assignment of monetary damages to compensate victims for their losses, and criminal fraud being punishable by jail time as well as by fines. For a fraud to be a criminal offense, it needs to have been in violation of either a federal
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: "Hohu. The question is: Hohu, and the city is: Hohu. We have: Hohu, and the city is: Hohu. Now is: Hohu, and the city
Most negative on
Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.
-
Central Business District and surrounding areas such as Braamfontein, Hillbrow, and Yeoville for more secured houses or offices in the Northern Suburbs. By the late 1990s, the Central<|endoftext|>A shoulder
-
and urban blight, many of the buildings are unoccupied as tenants have left for more secure locations in the Northern Suburbs, in particular Sandton and Rosebank. There are significant movements to revive the
-
of extraordinary contrasts, of glass and steel skyscrapers and fetid shantytowns, of internationally recognized universities and widespread illiteracy, of glittering abundance and
-
and⏎• increase learning opportunities outdoors.⏎Placing children’s well-being at the center of planning of the urban environment brings benefits – not only for children but for city dwellers of all ages. Child-friendly environments support inclusion, well-being, sustainability
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
- L3:1880 excites
- L3:1035 suppresses
- L3:1216 weakly suppresses
- L2:1071 weakly excites
- L3:2484 weakly excites
- L3:421 weakly suppresses
- L3:2359 weakly excites
- L3:2715 weakly suppresses
- L3:50 weakly excites
- L3:1390 weakly excites 'that' in 'so that' purpose clauses
- L3:2963 weakly suppresses "discrete" and "dispersive" in technical text
- L3:2976 weakly suppresses
- L2:1447 weakly excites
- L2:2868 weakly excites
- L3:2012 weakly suppresses
- L2:2809 weakly excites
- L3:1257 weakly suppresses
- L0:1188 weakly suppresses
- L3:1831 weakly excites
- L2:2713 weakly suppresses
- L3:1327 weakly suppresses
- L0:451 weakly suppresses
- L3:2369 weakly suppresses
- L2:370 weakly suppresses
Feeds later layers
- L7:2284 suppresses
- L5:206 suppresses
- L5:981 suppresses
- L5:2701 suppresses
- L16:2238 suppresses
- L6:511 suppresses
- L20:2861 suppresses
- L5:2698 weakly suppresses
- L5:2815 weakly suppresses
- L8:2606 weakly suppresses
- L12:1227 weakly excites
- L25:2863 weakly suppresses
- L11:1324 weakly suppresses
- L26:2247 weakly suppresses
- L11:598 weakly suppresses
- L10:1974 weakly suppresses
- L6:2236 weakly suppresses
- L23:1464 weakly excites
- L24:2496 weakly excites
- L22:1840 weakly suppresses
- L20:1163 weakly suppresses
- L14:1037 weakly excites
- L9:2496 weakly suppresses
- L11:1171 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
- Vict
- ViewItem
- viewDidLoad
- bac
- ��
- createView
- 是一部
- 战机
- 保驾
- lasting
Suppresses
- -town
- dale
- .qml
- folk
- neighbor
- nog
- reur
- neighborhoods
- gossip
- infix