unclear: mid-sentence tokens in web text
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 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 fires on a grab bag of word pieces in the middle of ordinary web sentences, such as a date, a URL slash, or the word after 'In this paper'. There is no clear shared theme, and the strongest examples are hard to tell apart. Turning it up made the text wander without a clear change of topic.
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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London: Volume 2. Originally published by Cassell, Petter & Galpin, London, 1878.⏎This free content was digitised by double rekeying. All rights reserved.⏎The Plague of 13
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radiation and chemotherapy to synergise the effectiveness of cancer treatment.⏎However, various problems in treating tumours with genetically engineered bacteria need to be addressed. In this review, we focus on the role of intratumoral bacteria
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fractals, dynamical systems, patterns of nature created through simple rules, and aesthetic graphics drawn from the universe of mathematics and art.⏎Chaos and Fractals is divided into six parts: Geometry and Nature; Attractors; Cellular Autom
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effect as lasting? Some believe not.⏎Taken from…. The Future of Education: Tablets vs. Textbooks http://mashable.com/2012/10/05/tablets-vs-textbooks/⏎They also say…. ‘
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portal/species/overview?p_p_spp=257336⏎This map is based on the maps available from
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meticulously documented. Known as "quantum tunneling," this strange phenomenon had previously been thought to occur only on very small scales.⏎In this paper I report instances of the spontaneous relocation of entire cats. Though cats are arguably quantal
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: What is the value of $ \frac{1}{1 + x} $ when x is 0? What is the value of $ \frac{1}{1 + x} $ when x is 0? What is the value
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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table with a specific name or index exists.⏎The following example retrieves a single table by name from the DataTableCollection.⏎Private Sub GetTableByName() ' Presuming a DataGrid is displaying more than one table, ' get its DataSet
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information about survivors could not be confirmed<|endoftext|>A simple example of HTML is:⏎<HTML> <HEAD> <TITLE>This is the Title</TITLE> </HEAD> <BODY
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of fields.⏎The project is a continuation of Suhr’s previous work on nanotubes, which was published in Nature Nanotechnology. In this previous work, Suhr tested the strength and fatigue behavior of carbon nanotubes. He collaborated with
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>>> len(s) 13 >>> >>> len("") 0 >>>⏎>>> >>> s3 = '' # empty string using single quotes >>> s3 '' >>> >>> s4 = "" # empty string using double quotes >>> s4 '' >>> ```
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
- L8:341 excites
- L8:639 excites
- L7:713 excites
- L7:2610 suppresses
- L7:1190 suppresses
- L3:480 suppresses
- L7:642 weakly suppresses
- L6:786 weakly excites
- L7:48 weakly suppresses
- L8:1306 weakly excites help-seeking 'I don't know' phrases
- L1:1690 weakly excites
- L3:107 weakly suppresses line breaks mid-sentence
- L8:2274 weakly excites
- L5:529 weakly suppresses
- L8:2011 weakly excites
- L4:494 weakly suppresses
- L8:2023 weakly excites
- L7:412 weakly excites
- L1:1042 weakly excites
- L6:1186 weakly excites
- L1:2443 weakly excites
- L3:553 weakly excites
- L2:2363 weakly excites
- L7:885 weakly excites
Feeds later layers
- L12:657 suppresses
- L10:280 suppresses
- L10:598 excites
- L13:205 excites
- L10:1471 suppresses
- L16:2524 excites
- L14:1236 suppresses
- L10:1272 weakly suppresses
- L10:1342 weakly suppresses
- L19:2805 weakly excites
- L20:2658 weakly excites
- L13:1606 weakly suppresses
- L13:2954 weakly excites
- L16:2063 weakly excites
- L16:978 weakly suppresses
- L13:1396 weakly suppresses
- L10:2000 weakly suppresses
- L12:1281 weakly suppresses
- L21:1521 weakly excites
- L24:1076 weakly excites
- L10:40 weakly suppresses
- L12:2921 weakly excites
- L10:1245 weakly suppresses
- L25:465 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
- angep
- '^$',
- ối
- leet
- ện
- jee
- ale
- CIÓN
- وية
- Rise
Suppresses
- 感受到
- 畹
- rica
- клад
- uffer
- chia
- ….
- holds
- 这条路
- 浆