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

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

Neuron 235 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: 3.9020. Min Act: -0.1700

Data Index: 139352 (C4 (Web Text))

Max Activating Token Index: 382

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Text #1

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Max Act: 3.8708. Min Act: -0.1700

Data Index: 1437462 (Python Code)

Max Activating Token Index: 321

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Text #2

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Max Act: 3.8082. Min Act: -0.1700

Data Index: 630385 (C4 (Web Text))

Max Activating Token Index: 186

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Text #3

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Data Index: 1197995 (C4 (Web Text))

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Text #4

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Data Index: 758611 (C4 (Web Text))

Max Activating Token Index: 794

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Text #5

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Data Index: 136741 (C4 (Web Text))

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Text #6

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Data Index: 1588997 (Python Code)

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Text #7

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Data Index: 47808 (C4 (Web Text))

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Text #8

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Data Index: 809990 (C4 (Web Text))

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Text #9

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Data Index: 594312 (C4 (Web Text))

Max Activating Token Index: 482

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Text #10

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Text #11

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Text #12

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Data Index: 405325 (C4 (Web Text))

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Text #13

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Data Index: 1066345 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 499888 (C4 (Web Text))

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Text #16

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Text #17

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Data Index: 826618 (C4 (Web Text))

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Text #18

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Max Act: 3.7456. Min Act: -0.1700

Data Index: 1025837 (C4 (Web Text))

Max Activating Token Index: 314

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Text #19

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Data Index: 715325 (C4 (Web Text))

Max Activating Token Index: 523

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