'of' after an abstract 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. 12 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 on the word 'of' (or 'to') right after a noun like 'concept', 'idea' or 'knowledge', where the next words name the topic. It went quiet, and sometimes negative, on 'for' in phrases like 'a physical keyboard for transcription'. Turning it up or down gave unrelated text.
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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or variables. The concept of correlation was employed to decide whether a significant relationship existed between the paired data. Furthermore
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test hypotheses and make predictions. You'll use Excel's Analysis Toolpak to perform t-tests as well as simple linear and multiple regression analysis.⏎required: basic knowledge of Excel; see Excel Basics⏎Monday, Oct. 13, 6
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of instruction where attention is given both to the language and the content” (Coyle et al 2010:3).⏎Historically, the idea of combining content and language learning (CLIL) comes from countries such as the USA
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7 2003|⏎ASJC Scopus subject areas⏎- Physics and Astronomy (miscellaneous)<|endoftext|>Most computer users are familiar with the concept of spyware — at
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free of processed and cooked food. Most raw food devotees also consume a mostly organic foods to avoid exposure to pesticides and other synthetic chemicals. The extent of adherence to these tenants is pending the level of commitment to adopting a “pure” version of
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to the mischief-making followers of those gods.⏎Polytheistic or non-literate cultures very often contain a belief 1n winged minor gods but the concept of the intermediary, wholly good angel was most fully developed in the West. Where there
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 20th of the 10th, the 10th of the 10th of the the 1 100th, the the 10th of the the 100
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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that fail to enter the system for annualized screening is closer to 70%, a leading contributor for breast cancer being the number #1 cause of cancer mortality for Asian women.⏎On all tissue types, of those patients who are diagnosed by mamm
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with a Veritas Prep instructor for a time, it’s a good idea for students to take another practice test.
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the conditions.<|endoftext|>Viewing page 28 of 101⏎It looks like you're using a mobile device. We recommend using a physical keyboard for transcription entry.⏎28 REPORT NATIONAL ADVISORY COMMITTEE FOR AERON
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Exercise 6.5⏎In NCERT Solutions for Class 10 Maths Chapter 6 Exercise 6.5, we have
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
- L4:4 suppresses
- L10:132 excites
- L11:31 suppresses
- L3:278 excites
- L5:5 weakly suppresses digit after a label like paper or type
- L7:8 weakly excites
- L6:345 weakly excites
- L0:1082 weakly suppresses
- L7:6 weakly suppresses
- L1:1300 weakly excites
- L9:29 weakly excites opening parenthesis before an acronym
- L9:1358 weakly excites
- L0:2832 weakly excites
- L10:189 weakly excites
- L6:1342 weakly excites
- L10:105 weakly suppresses
- L10:272 weakly suppresses
- L3:232 weakly excites 'on' after a noun like 'impact on'
- L4:16 weakly excites
- L4:1686 weakly excites
- L9:11 weakly excites
- L0:700 weakly suppresses
- L4:2923 weakly excites
- L5:871 weakly excites
Feeds later layers
- L22:489 suppresses
- L16:567 excites
- L16:109 excites
- L19:1464 suppresses
- L16:162 excites
- L17:1122 suppresses
- L16:507 excites
- L16:153 weakly excites
- L16:194 weakly excites
- L16:25 weakly excites
- L16:73 weakly excites
- L17:2196 weakly suppresses
- L13:132 weakly suppresses "of" after a noun
- L22:171 weakly suppresses
- L16:107 weakly excites
- L17:1223 weakly suppresses
- L16:127 weakly excites
- L16:105 weakly excites
- L16:110 weakly excites
- L16:53 weakly excites
- L16:549 weakly excites
- L16:26 weakly excites
- L15:2573 weakly suppresses
- L16:1040 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
- 诱人
- 子里
- etable
- 是韩国
- isable
- ining
- oystick
- ensen
- -double
- obby
Suppresses
- depth
- depth
- begin
- shore
- prime
- shi
- maturity
- conscious
- suspense
- اب