the word 'background'
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
This neuron lights up on the word 'background', whether it means the back of a picture, a screen colour, or a process running behind the scenes. Its negative side is weaker and points to words about being tired or fatigued. The written output when it was turned up did not clearly follow this 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.
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order to gather enough light so that dim, 12th (or even 13th or 14th) magnitude stars are visible in the background, making it possible to determine where the Cassini spacecraft is pointed on the sky
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for students to individualize the map with images, colors, background, and font. As Miles ‘23 noted, this<|endoftext|>The Bill states
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positions with the camera pointing at them from the start. The history then appears clear or with little texture as well as the design appears as a still photo. The background is additionally the sight in the picture since it adds rate of interest or drama.
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is driven by the simple fact that Apache is a hypertext⏎transfer protocol (HTTP) server that runs in the background as a daemon. Because⏎it is a daemon, it must do all the
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and set the contrast up all the way. Adjust brightness however you see fit. The idea is that you want the image to be black blotches on a white background, or vice versa. One will be the ocean, the other the land.
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das Caldeiras - in the foreground, the lava flows, then the cinder cone Pico Pequeno (1995) and in the background, the Pico do Fogo stratovolcano - photo © 2
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 problem of a function is to be found. If a function is oscillating or oscillating, the function is becoming difficult to keep with, it's a periodic function. So, the function is periodic, the function is becoming difficult to
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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- Faulty brakes⏎- Poor decisions regarding travel in bad weather⏎- Fatigued drivers⏎- Speed-limit violations⏎- Failing to yield⏎- Aggressive
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3_000_027⏎It was beginning to get dark, and the softly falling snow was blanketing the busy New York streets. Tired office workers and shoppers rushed to the waiting horse-drawn streetcars. A driver
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’s safety.⏎8 Drowning Myths⏎Myth: Good swimmers don’t drown.⏎Reality: Anyone can drown. Even the best swimmers, can tire, drift too far out, get a cramp, suffer an injury, or
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and the world’s heads of state have failed to solve the climate crisis or to shift into a green economy – all while everyone knows that the path we tread will exhaust the world’s food, water and energy. Public opinion strongly favors action; nonetheless
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
- L2:126 weakly excites
- L3:1062 weakly excites
- L2:75 weakly suppresses
- L2:70 weakly excites
- L3:464 weakly excites
- L2:92 weakly excites
- L3:691 weakly excites
- L3:2385 weakly excites
- L3:342 weakly excites
- L3:2598 weakly suppresses
- L1:2929 weakly excites
- L0:1224 weakly suppresses
- L2:2888 weakly excites
- L2:1742 weakly suppresses
- L3:870 weakly suppresses
- L1:1464 weakly excites
- L0:1301 weakly suppresses
- L3:2571 weakly excites
- L0:1055 weakly excites
- L3:144 weakly excites
- L3:2210 weakly excites
- L0:252 weakly suppresses
- L3:50 weakly excites
- L2:1657 weakly excites
Feeds later layers
- L5:1027 suppresses
- L24:2185 weakly excites
- L5:3042 weakly suppresses
- L5:55 weakly suppresses
- L6:2502 weakly suppresses
- L14:2686 weakly excites
- L12:2475 weakly excites
- L26:2629 weakly excites
- L24:1536 weakly excites
- L19:630 weakly suppresses
- L6:1101 weakly suppresses
- L12:2733 weakly excites
- L6:2128 weakly excites
- L5:2753 weakly suppresses
- L18:181 weakly excites
- L6:920 weakly suppresses
- L9:1843 weakly excites
- L5:2340 weakly excites
- L18:1844 weakly suppresses
- L20:1262 weakly excites
- L5:2220 weakly excites
- L13:2869 weakly suppresses
- L6:2701 weakly suppresses
- L12:3067 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
- -bg
- -background
- ooth
- ;background
- 心境
- /bg
- AVC
- :bg
- isto
- andbox
Suppresses
- alle
- .tell
- oton
- 场馆
- ore
- leur
- нер
- adders
- .failure
- 投放