'the' after 'in' or 'use'
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. 19 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 reacts to the word 'the' when it comes right after a preposition or verb such as 'in' or 'using', as in 'in the series' or 'use the module'. It is mostly quiet on other words. Turning it up or down changed the story's topic without a clear pattern.
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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information on Pilates in physical therapy and sports therapy click here.<|endoftext|>This course in the APHLIS series on postharvest loss measurements introduces you to the creation and
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mathematical problems when compared to those who focus on memorizing solutions. Problems like limit solving<|endoftext|>How to dissolve polygons spatially in GRASS GIS⏎You can use the v.dissolve module to
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switch to that directory.⏎If you wish to place the drive image in a specific folder, then navigate to it now. We’ll just place our drive image in the
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Scientific American Mind is a series of short video primers on the brain and how we feel, think and act. Below is a synopsis of the first video in the series written by a guest on this blog, Roni Jacobson, a science
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Approach 1: Unzip Using the .tar Utility⏎The most common method of decompressing a file on Linux
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researchers examined two major international apparel brands, Nike and Adidas, to determine the paths taken to reach corporate sustainability. Saheli Goswami, a doctoral student in the MU College of Human Environmental Sciences, says that while both companies are currently models of
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 the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the
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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IS) Manager by right clicking your server in Server Manager. You can add a website by right-clicking the Sites node in the tree and selecting Add Website. In the Add Website dialog box, you can enter a friendly name for your website.⏎
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/or remedies mentioned in this article. Yarrow is one of the oldest medicinal herbs, dating back thousands of years and used for various ailments. It’s a member of the aster family, along with chamomile and chrysanthemums;
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communication. The Recall option isn’t available for a communication displayed in the Reading Pane.⏎- Now from the Message tab, elect Conduct> Recall This Communication.⏎- In the Recall This Message dialog box, select one of the below options Cancel or Replace
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means that the files are stored in a compressed format.⏎For Python Implementation⏎You can use OpenCV to manipulate the images.⏎pip3 install opencv-python numpy⏎Open
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
- L18:2637 suppresses
- L17:1858 excites
- L14:1015 suppresses
- L18:1770 excites
- L18:848 suppresses
- L18:3028 suppresses
- L18:1894 excites
- L18:1790 suppresses
- L17:2480 suppresses
- L18:1664 suppresses
- L17:2565 weakly suppresses
- L17:418 weakly suppresses
- L11:1981 weakly suppresses
- L12:2235 weakly excites
- L13:2634 weakly excites
- L14:1219 weakly suppresses
- L18:3000 weakly suppresses
- L16:2839 weakly excites
- L18:1602 weakly suppresses
- L3:2972 weakly excites word endings in multi-token nouns
- L17:2036 weakly suppresses
- L18:2622 weakly suppresses
- L13:1006 weakly suppresses
- L17:250 weakly excites
Feeds later layers
- L20:769 strongly excites
- L20:955 excites
- L20:1112 excites
- L20:331 suppresses
- L21:336 excites
- L21:324 excites
- L20:439 excites
- L20:2025 suppresses
- L20:1406 excites
- L20:872 excites
- L20:1001 excites
- L20:375 suppresses
- L20:1195 excites
- L27:399 suppresses
- L26:507 suppresses
- L21:863 suppresses
- L21:404 excites
- L20:738 suppresses
- L20:1131 excites
- L23:348 excites
- L27:127 excites
- L21:457 excites
- L20:1677 excites
- L21:653 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
- `
- “
- ven
- `_
- “
- тер
- viz
- "
- gamma
- Between
Suppresses
- (QtCore
- уча
- ainer
- ług
- ój
- cá
- ','%
- Nokia
- 祧
- alink