mixed, weak code and reference hits
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. 21 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
Unclear. It fires weakly on a mix of things, like code objects, reference numbers and URLs, with no single clear pattern. Turning it up gave random-sounding text about news and value.
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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⏎But here thing is, save() method can return that primary key id value which is generated by hibernate and we can see it by⏎long s = session.save(k);⏎In this same case, persist() will never give any value back
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get its DataSet. Dim thisDataSet As DataSet = CType(DataGrid1.DataSource, DataSet) ' Get the DataTableCollection. Dim tablesCollection As DataTableCollection = thisDataSet.Tables ' Get a specific table by name. Dim table As DataTable = tablesCollection
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help Grade 2 students learn to tell and write time from analog and digital clocks to the nearest five minutes, using a.m. and p.m.⏎Common Core: 2.MD.7⏎
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0) ⇒ #<marker at 100 in markers.texi>⏎;; Now insert one character at the beginning of the buffer: (goto-char (point-min)) ⇒ 1 (insert "Q") ⇒ nil⏎<|endoftext|>A bead
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they all sitting? Can you find all the possible ways?⏎What is the best way to shunt these carriages so that each train⏎can continue its journey?⏎If you split the square into these
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.⏎Several species are considered commensals - dependent on the gopher tortoise burrow for refuge and microhabitat. These include gopher frogs (Rana capito) crickets, beetles and the Florida mouse (Podomys
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: I have a cycled type of that is with a pvalue and a type of data that is a big value on the edge, with a type of codel that is called a 'd' value. I think that the 'd
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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server that supports them. In the example, the client is requesting UTF-8 be the character set used for the response.⏎Accept-Datetime: The client uses this header to indicate that it wants a past state of this resource, as specified by
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lists the file formats that NMRView can read directly without the user needing to specify any parameters. Other file formats can be read by creating an NMRView parameter file that contains a description of the layout of the file.⏎|Program||Format
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this format or that format?⏎Sometimes you'll want all of these variations at the same time. In such cases, I have found that using a dict for your return value is a good solution. For instance, here is a piece of a doc
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urllib2.urlopen``. Per urllib2, it has an ``info()`` method⏎containing things like headers, etc.⏎Upon success, if you set ``parse_xml_document=True``, this will⏎contain the parsed xml_document. I
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
- L20:96 suppresses
- L20:900 excites end-of-text right after cut-off text
- L9:18 suppresses text boundary after a document break
- L15:524 excites
- L3:5 excites
- L16:270 suppresses
- L4:1 excites
- L9:26 excites
- L10:32 excites
- L7:3 suppresses
- L3:133 suppresses
- L15:1452 suppresses
- L5:2 suppresses
- L5:170 excites
- L19:1416 suppresses
- L9:11 suppresses
- L14:89 suppresses
- L18:735 suppresses
- L19:905 suppresses
- L18:109 weakly suppresses
- L1:1081 weakly suppresses
- L10:59 weakly suppresses
- L9:114 weakly suppresses
- L8:1320 weakly suppresses
Feeds later layers
- L25:14 suppresses
- L23:3 suppresses
- L22:2712 weakly excites
- L22:101 weakly suppresses
- L26:280 weakly suppresses
- L26:222 weakly suppresses
- L22:1717 weakly excites
- L25:69 weakly suppresses
- L22:2666 weakly excites
- L24:463 weakly excites
- L22:1864 weakly excites
- L23:206 weakly excites
- L27:104 weakly suppresses
- L25:1987 weakly excites
- L22:2886 weakly excites
- L22:100 weakly suppresses
- L27:1744 weakly excites
- L24:1500 weakly excites
- L22:116 weakly suppresses
- L22:70 weakly suppresses
- L22:2963 weakly excites
- L26:160 weakly suppresses
- L25:1353 weakly excites "in" before "good" condition
- L26:266 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
- ewear
- 荷
- ienza
- técnico
- це
- 管理局
- жение
- professionnel
- 的技术
- technological
Suppresses
- StateToProps
- `\
- uptools
- utoff
- `$
- StdString
- rowsing
- urlString
- appendTo
- ["$