unclear: verbs after a noun or 'that'
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. 19 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 is hard to pin down. It fires on verbs such as 'harvest', 'used', 'burn' and 'molting' that come right after a noun or 'that', but the pattern is loose. Steering did not produce a clear theme.
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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. As a result, farmers will be able to significantly reduce pesticide applications and harvest bigger yields. The crop is also expected to support the nation's economic development and
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structure is similar to that of the ___2___ and national governments, with an elected mayor as chief of the ___3___ and an elected council that ___4___ the various neighborhoods forming the ___5___ . The ___6___ appoints heads
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For cantaloupe, the principal harvest indices are surface color and the development of the abscission zone.⏎Most fruit vegetables are harvested by hand. Some harvest aids may be used, including pickup machines and conveyors
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not found anywhere else, and now rare even in Jordan; the Christian Bedouins.⏎Many of the traditional houses of Hmoud were built on caves that used to be a strong attraction for settling this site, as they provided early shelters prior
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be extremely stingy with neutrons. The coolant moderator combination had to be one that did not absorb neutrons to any great extent. To make natural uranium “burn” every available neutron has to find its way into fuel material. Using a neutron
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izing the cities.⏎Designing the board, deciding how to connect the cities⏎Creating their board based on having 6 players⏎Setting up the game to playtest it⏎“The city defence changes when
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 number 0 is often the number 000000000000000000000000000000000000000
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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while loop keeps running while the value of i is equal to or greater than 0.⏎- Inside the loop, we are printing the element for index i and decrementing the value of i by 1.⏎If you run this program, it
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⏎Create sequnce 1 4 9 16 25.........⏎Basics: Divide integers to get integer outputs in all cases⏎Determine value using Look-up table method⏎Create Volcano (or Atoll) mart
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plane is still on the ground, you design and develop measuring devices that take temperature, noise, altitude, navigation, and maneuverability readings. Then you hard-wire the devices into place, and send the Test Pilot into the clouds. When he
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progress over the years!⏎- Color and cut out the pieces.⏎- Roll the large triangular piece and use the tab to glue it into a cone⏎- Glue the nose onto the face using a dot of glue on the nose (this allows
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
- L18:1601 suppresses
- L16:739 excites
- L8:216 excites
- L18:229 excites
- L18:935 excites
- L18:2787 excites
- L6:375 suppresses
- L15:675 excites
- L16:2227 suppresses
- L11:153 suppresses
- L2:1282 excites
- L16:652 excites
- L2:491 excites
- L17:153 suppresses
- L14:1148 excites
- L4:48 suppresses
- L18:1516 suppresses
- L14:526 suppresses
- L16:1158 suppresses
- L18:2703 excites
- L17:1282 suppresses
- L17:1177 suppresses
- L14:1209 suppresses
- L16:2128 excites
Feeds later layers
- L20:593 strongly suppresses
- L20:1972 strongly suppresses 'of' in 'of course'
- L22:353 strongly excites
- L25:247 suppresses
- L20:728 suppresses
- L20:64 excites
- L22:1124 suppresses
- L22:197 excites
- L20:271 excites
- L24:49 excites
- L21:310 suppresses
- L20:544 suppresses
- L27:108 excites
- L20:331 excites
- L20:955 suppresses
- L23:96 excites
- L27:663 suppresses
- L20:482 suppresses
- L20:762 excites
- L27:121 excites
- L22:171 suppresses
- L26:139 excites
- L27:149 excites
- L20:94 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
- \Extension
- ieties
- Sikh
- ่อน
- umb
- ستان
- respectfully
- 构
- submits
- Dresses
Suppresses
- the
- them
- these
- those
- 它
- their
- everything
- our
- it
- ate