adjectives right before a noun
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. 1 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
This neuron fires on a single descriptive word, like 'lengthy', 'ordinary' or 'strange', that comes right before the thing it describes. Turning it up made the model's writing drift into random topics, so it does not seem to change the style much.
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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lengthy work experience in space. As part of three space missions, he has spent
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insulting when we imagine countries outside the West have something unique in their history where they crave
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refine, and establish clinical uses for liquid biopsy tests.⏎Different liquid biopsy<|endoftext|>Biology
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undeniable that teaching mathematics in the bilingual classroom, when the language of learning and teaching (
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ordinary panel. This manufacturing method significantly reduces the weight of the concrete panel, without any
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ordinary)⏎→ The two countries have resumed normal diplomatic relations.⏎→ Traffic was normal for
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 idea of a system that can be used in the real world. It is not just a computer, but it is more than a computer. It is a system, not just a program, but it is a program. It is a
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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patient’s ‘kidney history’ and leads into a description of the natural history and
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Server, loading data onto the LASR Analytic Server, and manipulating data on the
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Math and computer science teacher Myra Deister of Sunny Hills High in Fullerton didn
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server. Examples stock feeds, system status, weather conditions or other monitoring applications. This
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
- L0:2672 excites
- L0:2844 excites
- L0:2582 suppresses
- L0:1947 suppresses
- L0:2972 excites
- L0:2107 suppresses
- L0:1780 suppresses
- L0:552 excites
- L0:2877 suppresses
- L0:2415 suppresses
- L0:1838 suppresses
- L0:2425 excites
- L0:2242 excites
- L0:2857 suppresses
- L0:2440 suppresses
- L0:2293 excites
- L0:1905 suppresses
- L0:2785 suppresses
- L0:2918 suppresses
- L0:1224 suppresses
- L0:2639 excites unclear: weak hits on 'holiday' and 'playing', negative on 'Ada-fruit'
- L0:1793 weakly excites
- L0:1301 weakly suppresses
- L0:861 weakly suppresses
Feeds later layers
- L2:55 suppresses
- L2:1489 suppresses
- L2:128 suppresses
- L2:321 suppresses
- L2:646 suppresses
- L27:2172 excites
- L27:456 weakly excites
- L2:46 weakly suppresses
- L27:2863 weakly excites
- L16:2650 weakly suppresses
- L27:862 weakly excites
- L27:46 weakly excites
- L27:1458 weakly excites
- L18:191 weakly suppresses
- L27:2225 weakly excites
- L27:2573 weakly excites
- L2:816 weakly excites
- L27:28 weakly suppresses
- L2:2981 weakly excites
- L4:160 weakly suppresses
- L27:823 weakly excites
- L27:1175 weakly excites
- L15:419 weakly excites
- L3:763 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
- modifies
- [].
- кри
- 臾
- edException
- mutating
- 季后
- pronounce
- unarmed
- evolves
Suppresses
- work
- ail
- id
- term
- apple
- Company
- atti
- water