'over' meaning time or duration
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. 18 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 lights up on the word "over" when it means a span of time or a finished process, as in "over 700 years ago", "over the years" or "over and over". It is quieter on the opposite side, where it switches off for sentences that begin with "So". Turning it up did not produce a clear theme in the written continuations.
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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of Giza have been the objects of many conspiracies over the years. Many people believe that the Pyramids are a link to an ancient
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wondering? Well, think about analog watches. They keep time thanks to a mechanical architecture that siphons off kinetic energy from you moving about, and stores it over time. The team wondered if they could borrow principles like this in their own marvelous
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Detoxification – Part 1⏎Updated: Sep 24, 2018⏎Detoxification – you’ve heard this word many times over the last few years, but unless you have actually participated in a detoxification program
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with print. Get a newspaper delivered. Get her a library card and make the library a regular stop, like the grocery store and the dry cleaner. And get over your view of what "proper" book reading looks like — fiction, nonfiction
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/labs2.htm)View an example of a Dataforth test report that ships with each module.Remember, our Application Engineers can assist you with signal conditioner selection over the phone or via fax and email. Call us at our
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resolved, if we just try hard enough not to think about them, as if it were a choice to be impacted by our worst experiences, to relive them over and over again, and to react as if we were under threat.⏎Let’s
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: The way in the box, the way in the light, the way in the theme, and the like, that has been for a family, and for a person, and on the like, with the family, with the family, in
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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Use. The complexity and uncertainty of a Fair Use analysis make it both risky and cumbersome to apply to small projects involving borrowing Internet materials<|endoftext|>3D Television Technology⏎So, you’ve seen it on the news, read about it in the papers and
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But what exactly is Diabetes? There are a lot of myths and misunderstandings surrounding the disease, particularly when it comes to type 1 versus type 2.⏎So let’s start with
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The Sound of Silence” to “Bridge Over Troubled Water”, their songs act<|endoftext|>Read Music Notes⏎How to Read All the Music Notes -- With Ease⏎So
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?⏎As one of the lesser known grains out there, buckwheat (and what it is good for) can often be a point of confusion for many. So, before we get any further – we first think that it would be a good
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
- L17:213 strongly suppresses
- L16:177 strongly excites zero digit inside dates and codes
- L2:1795 strongly suppresses
- L5:1546 strongly suppresses
- L0:44 strongly suppresses
- L10:1052 strongly suppresses
- L1:15 strongly suppresses
- L4:498 strongly suppresses
- L1:178 suppresses
- L0:1241 excites
- L0:1906 suppresses
- L7:1337 excites 'of' inside organisation and product names
- L2:1463 excites
- L16:164 excites
- L17:1046 suppresses
- L16:827 suppresses
- L0:2302 excites
- L15:381 excites
- L17:337 suppresses
- L7:342 excites
- L15:1616 weakly excites word fragments mid-word
- L16:1066 weakly suppresses
- L15:1404 weakly suppresses
- L15:1587 weakly excites
Feeds later layers
- L20:392 strongly suppresses
- L21:381 strongly suppresses zeros inside long number codes
- L20:2206 strongly suppresses
- L19:1370 strongly suppresses
- L20:3008 strongly suppresses
- L20:2261 strongly suppresses
- L21:2826 strongly suppresses
- L20:2363 suppresses
- L23:2981 suppresses
- L23:1324 suppresses
- L19:843 suppresses
- L19:1696 suppresses
- L19:906 suppresses
- L20:1374 suppresses
- L21:1052 suppresses mid-word 'electro' and 'ro' fragments
- L19:798 excites
- L27:1585 suppresses
- L21:2302 suppresses
- L22:2365 suppresses
- L26:1290 excites
- L27:2149 suppresses
- L19:390 excites
- L26:2846 suppresses
- L19:316 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
- faculties
- Hundreds
- insula
- alore
- pylint
- uent
- ▇
- /xhtml
- 昂
- ⏎ ⏎
Suppresses
- ongan
- iginal
- entimes
- ставить
- ductive
- Letter
- WithTag
- aurus
- sid
- petition