'the' inside a phrase, mid-sentence
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 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 lights up on the word 'the' in the middle of a sentence, right before a noun phrase like 'the students' or 'the conversion'. When it was turned down, the model tended to repeat 'the' over and over, and turning it up made the text wander without a clear theme.
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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and defending their Homeland.⏎The Vice-Rector for Educational Work, Social Development and Public Relations, Alesya Kuznetsova, addressed the students with the words: “80 years ago, on this morning of June 22
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. There are several questions in this exercise. Our subject expert teachers have solved each of these questions in a step by step manner. All these solutions are beneficial for the students of class 10 appearing for the board exams. Students can easily NC
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, worthy of making his acquaintance? Who are the bad ones whom one should avoid until they change their ways?⏎There is a common Chinese saying; A fence needs the support of three stakes, an able fellow needs the help of three other people.
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ads6x98y<|endoftext|>Arabic Numeral 1 in Roman Numerals converter tool is available here. This tool can prove to be very handy in the conversion of Arabic to Roman numerals. The tool basically works on a very simple
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in the household because it has the ability to provide very strong bonds. The epoxy is marketed for use at home and
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important topics related to the chapter are covered in the following exercises.<|endoftext|>What you will learn in this module⏎Understand different tasks that have to be done in the groups⏎Address issues related to overburdening of a leader⏎Emphas
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 one of the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the 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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Here I am setting my command name with “DOSBox” So I am able to open it using this command name in the run.⏎after typing the name of the command, click on the finish.⏎Step 4: Finishing
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which operates to trip the circuit breaker.⏎Email Based, Online Homework Assignment Help in Classification Of Relays⏎Transtutors is the best place to get answers to all your doubts regarding classification of relays with examples. Transtutors has a vast
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10 Maths Chapter 6 Triangles Exercise 6.5 are given here. There are several questions in this exercise. Our subject expert teachers have solved each of these questions in a step by step manner. All these solutions are beneficial for the
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5 times the length of the head; they are located almost on the upper profile of the head. Mouth large, oblique, not protruding. The tip of the upper jaw is set behind a vertical line passing through the posterior edge of the
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
- L18:476 excites
- L18:755 suppresses
- L18:646 suppresses
- L10:556 excites
- L18:1225 excites
- L18:804 suppresses
- L18:1231 excites
- L17:6 excites
- L17:947 excites
- L17:714 weakly suppresses
- L18:1595 weakly excites
- L10:1289 weakly suppresses
- L18:177 weakly suppresses
- L10:1278 weakly suppresses
- L17:56 weakly excites
- L4:236 weakly excites
- L3:615 weakly suppresses
- L3:805 weakly suppresses
- L9:812 weakly excites
- L16:1652 weakly suppresses
- L3:198 weakly suppresses
- L17:593 weakly excites
- L9:530 weakly suppresses
- L2:619 weakly suppresses
Feeds later layers
- L27:127 strongly excites
- L26:507 strongly suppresses
- L27:399 strongly suppresses
- L21:863 strongly suppresses
- L20:2278 suppresses
- L24:49 excites
- L20:738 suppresses
- L21:758 suppresses
- L23:94 excites
- L20:375 suppresses
- L22:171 suppresses
- L24:2538 excites
- L27:121 excites
- L27:1382 suppresses
- L27:2537 excites
- L25:1796 suppresses
- L26:251 excites
- L20:2729 suppresses
- L22:103 suppresses
- L25:1586 excites
- L25:45 weakly suppresses
- L27:2084 weakly suppresses
- L24:918 weakly excites
- L25:2531 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
- robe
- ื
- ictionaries
- ismatic
- block
- iction
- arden
- st
- 也是一个
- ẫ
Suppresses
- the
- the
- _the
- →the
- The
- -the
- THE
- —the
- _THE
- nThe