day number in dates
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. 9 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 fires weakly on the spot where the day number goes in a date, such as 'Published on Jan 10, 2016'. It is a weak signal, and turning it up did not produce a clear theme in the written text.
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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Quite naturally, it will take some time for these acquisitions to start making a positive impact on revenue and, by<|endoftext|>Laser Ignition System⏎Published on Jan 10, 2016⏎Economic as well
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Digitals by Danielle Thompson Chalkboard Paper Kit. Fonts used: school script dashed, Rudiment and Homemade Apple.⏎Posted by Craftyminx on October 12, 2011 at
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) Limited, Delta, BC, Canada (Martyr Brand), www.canmet.com<|endoftext|>5 interesting facts about the Singapore River clean-up⏎Published on Jul 5, 2014 6:00 AM⏎The heavily
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phosis⏎Updated: Mar 25, 2022⏎Your spine consists of a series of
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closed.<|endoftext|>The bittersweet truth about how taste works⏎Scientists have discovered an ion channel that allows taste buds to communicate with the brain.⏎Wed, Mar 06, 2013 at 03:20 PM
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Yes, my child is one of the 12 percent--now what are we going to do about it?"⏎How about it?<|endoftext|>Published on Feb 20, 2013⏎CBS News RAW: A new eruption
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 difference in the difference of two things" - the difference of two things - the difference of two things - the difference of two things - the difference in the same things - the difference in the same things - the difference in the same
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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this topic I highly recommend reading Bruce Rogers' post:⏎Good study for the Moxy people. I did a post and review on that article. https://t.co/D9NIorgXuc— Bruce Rogers (@bjrmd) August
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% of the stories) and Dashkat Hakaayuʔ “Whitebread” (who told 19% of the stories) https://archive.org/details/traditionsofcadd00dorsrich⏎Explore more about the
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with each Dataforth SCM. Dataforth test instruments are calibrated and traceable to NIST standards. (see NIST info at: http://www.nist.gov/public_affairs/labs2.htm)View an example of a Dataforth test
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so arranged that the first blow for each hour shall be accurate to the second of time." No clockmaker thought it remotely possible to<|endoftext|>by George Heymann | @te
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
- L8:7 excites
- L8:3 weakly excites
- L7:2316 weakly excites
- L8:567 weakly excites
- L1:188 weakly excites
- L8:388 weakly suppresses
- L2:1250 weakly suppresses
- L0:28 weakly suppresses
- L4:56 weakly excites
- L8:2879 weakly suppresses
- L0:1718 weakly excites
- L1:1487 weakly suppresses
- L4:1408 weakly excites
- L3:1117 weakly suppresses
- L6:925 weakly suppresses
- L6:1520 weakly suppresses
- L8:4 weakly excites
- L5:1187 weakly excites
- L0:2145 weakly excites
- L5:922 weakly suppresses
- L1:1374 weakly excites
- L7:2831 weakly suppresses
- L5:2757 weakly suppresses
- L7:247 weakly suppresses
Feeds later layers
- L20:1356 weakly excites
- L13:2601 weakly suppresses
- L16:1013 weakly suppresses
- L16:676 weakly suppresses
- L15:407 weakly suppresses
- L22:1738 weakly excites
- L13:2898 weakly suppresses
- L15:1927 weakly excites
- L19:1549 weakly excites
- L21:1801 weakly excites
- L23:59 weakly suppresses
- L21:180 weakly suppresses
- L14:1864 weakly excites
- L11:2387 weakly suppresses
- L14:3017 weakly excites
- L11:2986 weakly excites
- L13:1733 weakly excites
- L12:1861 weakly excites
- L16:1406 weakly excites
- L14:1304 weakly excites
- L23:1655 weakly excites
- L10:1266 weakly excites
- L15:2399 weakly suppresses
- L14:2615 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
- ote
- AccessException
- andes
- 能在
- otta
- acı
- фор
- over
- -over
- кон
Suppresses
- onica
- $ ⏎
- ruled
- uchos
- 两者
- aan
- REW
- ') ⏎
- ério
- _imag