"the" right after an action verb
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" when it comes right after an action word in instructions, such as "Divide the total", "Use the method" or "set the variable". The effect on the model's writing was not clear when turned up.
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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the total weight of the vehicle and its maximum load.⏎- Add an additional 25 percent of the total weight to allow a margin of error.⏎- Divide the total weight including the additional 25 percent by the number of wheels supporting the
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string, it is returned. Otherwise a case-insensitive search is performed, and if a DataTable name is found that matches this search, it is returned.⏎Use the Contains method to determine whether a
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- Your second subroutine should be called getVolumeOfCuboid(), take three parameters called width, length and height and apply the relevant formula to calculate and return the volume of a cuboid based on the given dimensions.<|endoftext|>Approximately 3
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over it is more convenient to create a script that can run all the commands with one message from you.⏎% filename simple.m⏎ini=1.; %set the variable ini to 1.⏎y0=ini; %set the initial condition
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Add “c:\Borland\Bcc55\bin” to the existing path⏎- Create a bcc32.cfg file which will set the compiler options for the Include and Lib
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concatenated.⏎You can create a RAID 5 volume without having to “zero out” the data blocks. To do so, do one of the following:⏎Use the metainit command with the -k option. The -k option recreates
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 need for a good education system. The need for a good education system. And so many people, including my parents, including my friends, including my family, are so many people, including my friends, including my family, are so
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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investors will also skip companies who don’t engage in socially responsible behavior (like coffee/restaurant companies who don’t use fair trade beans, for
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to bring man's esteemed friend into the postindustrial age of the genome. Compared with the Human Genome Project, the
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a generation of socially responsible society.⏎Third, the schools/universities, by having a standard curriculum,
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glimpse into the academic world and its view of religion in general and Hinduism in particular. The
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
- L21:1608 weakly suppresses
- L25:2547 weakly excites
- L16:622 weakly suppresses
- L8:2125 weakly suppresses
- L7:593 weakly excites
- L9:1542 weakly suppresses
- L12:122 weakly excites unclear: word before a clause continues
- L15:1843 weakly suppresses
- L25:2074 weakly suppresses
- L13:1996 weakly suppresses
- L4:941 weakly excites
- L10:2703 weakly suppresses
- L4:499 weakly excites
- L20:2634 weakly excites
- L23:2676 weakly excites
- L7:725 weakly excites
- L15:1689 weakly suppresses
- L25:1132 weakly excites
- L13:483 weakly suppresses
- L4:2259 weakly suppresses
- L23:541 weakly suppresses
- L6:1572 weakly excites
- L24:1343 weakly excites
- L9:903 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
- PackageName
- setC
- pheric
- ServiceImpl
- -Pack
- importing
- packageName
- sims
- realistically
- pics
Suppresses
- __(*
- itet
- or
- ift
- autom
- minster
- nor
- /qt
- 座
- entral