'have' after 'you' or 'to'
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 responds to the word 'have' when it comes right after 'you' or 'to', as in 'make sure you have' or 'once you have the value'. It is strongly suppressed by 'take on' in phrases like 'never takes on the same value'. Turning it up made the text wander into unrelated, rambling sentences.
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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to find the value of the mark. You can do this by using a percentage calculator. You can use it to find the value of a number. Once you have the value, you can write it down in terms of the percent. It’s
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service of: ASD at NASA / GSFC⏎& Michigan Tech. U.<|endoftext|>Troubleshooting With Superheat, Subcooling⏎You also need to have the right tools and know-how to apply these principles to use the tool quickly and
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– dd will copy every bit of it, even if there’s only one tiny file stored on the whole hard drive. So, to start, make sure you have a device connected to your computer that will be
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one time, make sure you have all the supplies you need at hand.⏎A lot of nurseries, garden centres
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. Test the alarm often to be sure it’s working properly. Replace the entire smoke detector every 10 years.⏎- Make sure you have enough smoke detectors in your house. Position them inside or just outside bedrooms, in
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are the part of same Microsoft exchange server.⏎How do I know if a recalled communication was successful in outlook?⏎Make sure you have to tick the following option when recalling the email. Outlook will send you a notice
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 position of a single person in a position of the form of a single person in the form of a single person in the form of a single person in the form of a single person in the form of a single person in the form of
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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with are called one-to-one functions. DEFINITION A function is called a one-to-one function if it never takes on the same value twice; that is, If a horizontal line intersects the graph of
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1 FUNCTIONS AND MODELS Not all functions possess inverses. Lets compare the functions and whose arrow diagrams are shown in Figure 1. Note that never takes on the same value twice (any two inputs in have different outputs), whereas does take
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Gambling operates according to conditioning principles, with emotional and social rewards playing a role as well as financial ones. The sights, sounds and other stimuli associated with gambling take on some of the same rewarding properties and thereby act as incentives in themselves, deepening
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until this point, his paintings were of peasant life in sombre colours. Once settled in Paris, however, his paintings took on new painting styles and brighter colours, and he started painting urban and suburban subjects.
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
- L3:2551 weakly excites
- L3:2096 weakly excites
- L1:325 weakly excites
- L0:963 weakly excites
- L0:1026 weakly excites
- L2:1095 weakly suppresses
- L3:2249 weakly excites
- L1:2335 weakly excites
- L3:632 weakly suppresses
- L3:1609 weakly excites
- L0:1920 weakly suppresses
- L3:1057 weakly suppresses
- L2:2818 weakly suppresses
- L3:1218 weakly suppresses
- L3:754 weakly excites
- L2:2804 weakly suppresses
- L3:59 weakly excites
- L0:1447 weakly excites
- L0:1347 weakly excites
- L2:546 weakly excites
- L3:2859 weakly excites
- L0:2163 weakly suppresses
- L3:878 weakly suppresses 'of' after 'Because'
- L3:2140 weakly suppresses
Feeds later layers
- L8:2764 suppresses
- L12:1475 excites
- L9:2196 weakly suppresses
- L14:1017 weakly suppresses
- L15:2682 weakly suppresses
- L5:267 weakly suppresses
- L23:1481 weakly suppresses
- L6:2310 weakly suppresses
- L15:1223 weakly suppresses
- L15:1951 weakly excites
- L21:2626 weakly excites
- L10:886 weakly suppresses
- L14:1219 weakly suppresses
- L7:2420 weakly suppresses
- L17:1107 weakly suppresses
- L8:2458 weakly excites
- L9:1795 weakly suppresses
- L9:2164 weakly suppresses
- L9:1748 weakly suppresses
- L5:2354 weakly excites
- L14:2776 weakly excites
- L7:2541 weakly suppresses
- L5:2898 weakly suppresses
- L16:2286 weakly 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
- aktion
- filtr
- proj
- 滤
- 捣
- jal
- 炉
- 담
- 终
- 在哪里
Suppresses
- زا
- ITIVE
- "He
- ductive
- казал
- ests
- “He
- hữu
- natural
- itated