Neuron Explorer

Qwen3-0.6B

the word 'data' in database contexts

A neuron in layer 6 of Qwen3-0.6B. Its strongest snippets are fairly consistent: several of them peak on the same token. It is featured, so it has steering outputs.

What this neuron does

This neuron responds to the word 'data' and nearby words used in computing and databases, such as 'data objects' or 'layouts'. Turning it up did not produce a clear theme in the model's writing.

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 activation was highest. Amber marks positive activation; the outlined token is the peak. Hover a token for its strength.

  1. #1 peak

    determine which features are currently being utilized to create structured data. Additionally, determine which features aren’t being utilized; if no validation rules, record types, or page layouts have been defined, then<|endoftext|>Over many decades, now, a popular idea across

  2. #2 peak

    happens⏎In Salesforce and most other CRMs, the origin of dirty data can usually be pinpointed by one or more of the following behaviors:⏎- Importing data from varying sources that lack proper structure or formatting rules⏎- Adding data that lacks

  3. #3 peak

    Create a new data directory.⏎Copy an existing data directory.⏎The following discussion provides more detail about each method.⏎Normally, you should never have two servers that update data in the same databases. This may lead to unpleasant surprises if your operating system does

  4. #4 peak

    of use and because a simple application tends to grow in complexity with time.⏎The global pattern to follow is MVC and the layering:⏎(View & Controller)⏎|View||HTML templates usually generated using a template engine|⏎|Input Controller||Filter and

  5. #5 peak

    |Listener||Contains a method that handles an event|⏎|Entity||Data object with identity (ID), for example “User”|⏎|Collection||Set of data objects|⏎|Value Object||Data object without identity, for example “Date”

  6. #6 peak

    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 to

Steering

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.

turned down a lot
Prompt

Here is something I have been thinking about lately: "I am a student who has to be a member of a club, and the club has a name and a number. Each book can be published by a single author, with a price and a category. A customer can order a book

Most negative on

Where the activation went furthest below zero. Blue marks negative activation. Many neurons mean something different in each direction.

  1. #1 peak

    Get the DataTableCollection. Dim tablesCollection As DataTableCollection = thisDataSet.Tables ' Get a specific table by name. Dim table As DataTable = tablesCollection("Suppliers") Console.WriteLine(table.TableName) End Sub⏎Available since 1.1<|endoftext|>

  2. #2 peak

    times the With clause is used in oracle .⏎(The aggregation SQL statement)⏎(query name sub-query_name);⏎Real life example 1 :⏎Let us take the example of Student table.If user wants to find out

  3. #3 peak

    all product categories. Some product categories have multiple packs but not all product categories.⏎If the one list has to

  4. #4 peak

    resents a relevant event in the domain|⏎|Listener||Contains a method that handles an event|⏎|Entity||Data object with identity (ID), for example “User”|⏎|Collection||Set of data objects|⏎|Value Object||Data object

Connections

Show on map

Which neurons in earlier layers feed this one, and which later ones it feeds. Amber links excite, blue links suppress; longer bars are stronger.

Fed by earlier layers

  1. L3:547 suppresses
  2. L5:1822 suppresses
  3. L5:133 excites
  4. L5:26 weakly excites
  5. L4:6 weakly suppresses
  6. L4:144 weakly suppresses
  7. L5:257 weakly excites
  8. L2:210 weakly excites
  9. L4:2969 weakly suppresses
  10. L5:222 weakly suppresses
  11. L1:812 weakly suppresses
  12. L5:158 weakly suppresses
  13. L5:2128 weakly excites
  14. L4:806 weakly suppresses
  15. L2:29 weakly suppresses
  16. L5:704 weakly excites
  17. L5:48 weakly excites
  18. L0:810 weakly excites
  19. L0:604 weakly suppresses
  20. L5:1965 weakly suppresses
  21. L4:1530 weakly excites 'see' in 'let's see' and 'to see if'
  22. L0:941 weakly excites
  23. L3:860 weakly suppresses
  24. L2:2355 weakly suppresses

Feeds later layers

  1. L9:958 excites
  2. L9:364 suppresses
  3. L9:1042 suppresses
  4. L9:1004 excites
  5. L10:1994 weakly suppresses
  6. L9:2548 weakly suppresses
  7. L7:1420 weakly suppresses
  8. L20:2171 weakly excites
  9. L22:1075 weakly suppresses
  10. L17:2541 weakly excites comma before but also in not only constructions
  11. L12:2359 weakly excites
  12. L17:2462 weakly excites
  13. L18:22 weakly suppresses
  14. L19:1925 weakly excites
  15. L22:1438 weakly suppresses
  16. L15:1564 weakly suppresses
  17. L9:1272 weakly suppresses
  18. L18:885 weakly excites
  19. L10:2054 weakly suppresses
  20. L7:95 weakly suppresses
  21. L25:2781 weakly excites
  22. L22:2261 weakly excites
  23. L20:2686 weakly excites
  24. L8:2809 weakly suppresses

Activation histogram

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.

1 values between -0.83 and -0.801 values between -0.69 and -0.661 values between -0.66 and -0.621 values between -0.62 and -0.582 values between -0.55 and -0.511 values between -0.51 and -0.483 values between -0.48 and -0.443 values between -0.44 and -0.415 values between -0.41 and -0.378 values between -0.37 and -0.3417 values between -0.34 and -0.3029 values between -0.30 and -0.2633 values between -0.26 and -0.2361 values between -0.23 and -0.19132 values between -0.19 and -0.16158 values between -0.16 and -0.12232 values between -0.12 and -0.09292 values between -0.09 and -0.05413 values between -0.05 and -0.01526 values between -0.01 and 0.02453 values between 0.02 and 0.06412 values between 0.06 and 0.09300 values between 0.09 and 0.13259 values between 0.13 and 0.16190 values between 0.16 and 0.20142 values between 0.20 and 0.2495 values between 0.24 and 0.2749 values between 0.27 and 0.3136 values between 0.31 and 0.3421 values between 0.34 and 0.3813 values between 0.38 and 0.4111 values between 0.41 and 0.456 values between 0.45 and 0.482 values between 0.56 and 0.59offnegativepositiveoften

Logit lens

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 layers instead.

Promotes

  1. onation
  2. 出来的
  3. альное
  4. 慣
  5. untos
  6. unofficial
  7. обы
  8. .DropTable
  9. opportunità
  10. religious

Suppresses

  1. Sq
  2. ämp
  3. seller
  4. ursion
  5. Sq
  6. vant
  7. BER
  8. averse
  9. ACTER
  10. #__