unclear: mid-sentence function words
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. 7 of Qwen3-0.6B. Its strongest snippets are mixed: they peak on different tokens. 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 strongest moments are scattered across unrelated sentences, often on small connecting words like 'as', 'being' or 'rapidly' in the middle of a phrase. No clear topic stands out, and the model's written output under steering does not show a clear theme either.
Written by Claude from this neuron's activations and steering outputs. Confidence: low. 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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with pH ranging from 4.40 to 7.45, a fish survey, including interviews
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and quality of bottled water must be as stringent as the EPA regulations which govern tap water.⏎To suggest in any way that
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diploma. Paying for college, however, has become a daunting task and strain for many American students and families. The cost of higher education across the country is rapidly increasing, at almost double the rate of inflation, outpacing increases in financial
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andela sat in a conference room at CERN and watched with his arms folded as his colleagues presented the latest results on the hunt for the Higgs boson
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our books but the layout of our collection is much more light, airy and spacious. Following on from Education, I’ve been taking
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frey, E.Godfrey@stfc.ac.uk⏎Research date: December 2008⏎E Godfrey et al., in Metal
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: I am thinking of the number 1, and I have a lot of things. What is the value of the number 2, and I have a lot of things. Let's see, so I can have some of them. 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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bounciness up to 1.⏎- Now select the ball, and go to the Physics tab. Also click ‘Rigid Body’ and leave the type as ‘Active’. We want this to simulate animation. Now change the bounciness
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to problems such as heart or lung damage, or even an increased risk of another cancer later on. Doctors do everything they<|endoftext|>Variety of electromagnetic radiation with frequencies between a few and a few hundred quadrillion oscillations per second, corresponding to wave
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but with poverty rates at record highs, programs like Social Security, Medicare, the Supplemental Nutrition Assistance Program
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issolved output=gadm36_dissolved_nocats option=del⏎Then, add unique categories to them.⏎v.category input=gadm3
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
- L5:585 excites
- L3:399 suppresses
- L5:1599 suppresses
- L6:323 suppresses
- L6:984 suppresses
- L6:1849 excites
- L5:565 suppresses
- L6:1753 excites
- L5:683 suppresses
- L6:1139 weakly suppresses
- L5:117 weakly excites
- L6:1348 weakly suppresses
- L4:24 weakly excites
- L6:2343 weakly suppresses
- L6:2539 weakly suppresses
- L6:16 weakly excites
- L6:698 weakly suppresses
- L6:12 weakly excites
- L4:302 weakly excites blank slot before a number
- L6:130 weakly excites
- L5:57 weakly suppresses
- L6:1971 weakly suppresses
- L6:936 weakly excites
- L3:922 weakly suppresses
Feeds later layers
- L11:2304 suppresses
- L8:170 excites
- L10:647 suppresses
- L12:1170 suppresses
- L8:469 suppresses
- L15:1210 suppresses
- L10:463 suppresses
- L8:190 suppresses
- L9:1370 excites
- L15:2383 suppresses
- L10:2944 excites
- L15:2326 suppresses
- L14:1693 excites
- L10:724 excites
- L10:144 excites
- L14:1769 suppresses
- L11:1533 suppresses
- L12:1798 excites
- L9:292 suppresses unclear: weak scattered tokens
- L12:305 suppresses
- L15:2137 suppresses
- L8:131 suppresses
- L14:305 suppresses
- L9:1563 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
- 独
- côt
- 她
- aint
- 獨
- endcode
- ','#
- ered
- 之称
- nt
Suppresses
- olkien
- хи
- roys
- ủng
- 咩
- vik
- -room
- 一件事情
- ompiler
- AGER