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

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

Neuron 40 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: 3.7755. Min Act: -0.1700

Data Index: 1128435 (C4 (Web Text))

Max Activating Token Index: 275

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Text #1

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Max Act: 3.7129. Min Act: -0.1700

Data Index: 814660 (C4 (Web Text))

Max Activating Token Index: 666

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Text #2

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Max Act: 3.6816. Min Act: -0.1700

Data Index: 1112654 (C4 (Web Text))

Max Activating Token Index: 219

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Text #3

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Max Act: 3.6816. Min Act: -0.1700

Data Index: 1025014 (C4 (Web Text))

Max Activating Token Index: 190

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Text #4

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Max Act: 3.6503. Min Act: -0.1700

Data Index: 763516 (C4 (Web Text))

Max Activating Token Index: 559

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Text #5

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Data Index: 13788 (C4 (Web Text))

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Text #6

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Data Index: 445202 (C4 (Web Text))

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Text #7

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Data Index: 870552 (C4 (Web Text))

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Text #8

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Data Index: 1000405 (C4 (Web Text))

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Text #9

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Data Index: 597331 (C4 (Web Text))

Max Activating Token Index: 547

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Text #10

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Data Index: 170430 (C4 (Web Text))

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Text #11

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Data Index: 62236 (C4 (Web Text))

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Text #12

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Data Index: 442308 (C4 (Web Text))

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Text #13

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Data Index: 505092 (C4 (Web Text))

Max Activating Token Index: 432

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Text #14

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Text #15

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Data Index: 124219 (C4 (Web Text))

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Text #16

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Data Index: 999972 (C4 (Web Text))

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Text #17

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Data Index: 1021644 (C4 (Web Text))

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Text #18

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Max Act: 3.5564. Min Act: -0.1700

Data Index: 293764 (C4 (Web Text))

Max Activating Token Index: 601

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Text #19

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Max Act: 3.5564. Min Act: -0.1700

Data Index: 754584 (C4 (Web Text))

Max Activating Token Index: 623

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