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Model: GELU Model: 3 Layers, 2048 Neurons per Layer

Dataset: 80% C4 (Web Text) and 20% Python Code

Neuron 1274 in Layer 1

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-3l')



Text #0

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Max Act: 5.3170. Min Act: -0.1700

Data Index: 321434 (C4 (Web Text))

Max Activating Token Index: 781

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Text #1

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Data Index: 625809 (C4 (Web Text))

Max Activating Token Index: 280

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Text #2

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Max Act: 5.2232. Min Act: -0.1700

Data Index: 18088 (C4 (Web Text))

Max Activating Token Index: 234

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Text #3

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Max Act: 5.2232. Min Act: -0.1700

Data Index: 555630 (C4 (Web Text))

Max Activating Token Index: 857

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Text #4

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Data Index: 286691 (C4 (Web Text))

Max Activating Token Index: 386

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Text #5

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Data Index: 1469622 (Python Code)

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Text #6

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Data Index: 949553 (C4 (Web Text))

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Text #7

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Data Index: 1165427 (C4 (Web Text))

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Text #8

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Data Index: 97239 (C4 (Web Text))

Max Activating Token Index: 980

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Text #9

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Data Index: 70744 (C4 (Web Text))

Max Activating Token Index: 207

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Text #10

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Data Index: 553140 (C4 (Web Text))

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Text #11

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Data Index: 733482 (C4 (Web Text))

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Text #12

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Data Index: 611111 (C4 (Web Text))

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Text #13

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Data Index: 1205823 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 208826 (C4 (Web Text))

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Text #16

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Text #17

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Data Index: 672915 (C4 (Web Text))

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Text #18

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Max Act: 5.1607. Min Act: -0.1700

Data Index: 822163 (C4 (Web Text))

Max Activating Token Index: 657

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Text #19

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Data Index: 1435970 (Python Code)

Max Activating Token Index: 338

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