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Model: GELU Model: 2 Layers, 2048 Neurons per Layer

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

Neuron 1769 in Layer 1

Load this data into an Interactive Neuroscope

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-2l')



Text #0

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Max Act: 3.7358. Min Act: -0.1700

Data Index: 211904 (C4 (Web Text))

Max Activating Token Index: 148

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Text #1

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Max Act: 3.6106. Min Act: -0.1700

Data Index: 1035313 (C4 (Web Text))

Max Activating Token Index: 419

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Text #2

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Max Act: 3.5793. Min Act: -0.1700

Data Index: 67667 (C4 (Web Text))

Max Activating Token Index: 985

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Text #3

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Max Act: 3.5166. Min Act: -0.1700

Data Index: 562812 (C4 (Web Text))

Max Activating Token Index: 768

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Text #4

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Data Index: 1331943 (C4 (Web Text))

Max Activating Token Index: 293

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Text #5

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Data Index: 1331152 (C4 (Web Text))

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Text #6

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Data Index: 1103271 (C4 (Web Text))

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Text #7

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Data Index: 1413869 (Python Code)

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Text #8

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Data Index: 662288 (C4 (Web Text))

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Text #9

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Data Index: 476813 (C4 (Web Text))

Max Activating Token Index: 300

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Text #10

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Data Index: 800353 (C4 (Web Text))

Max Activating Token Index: 811

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Text #11

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Data Index: 684129 (C4 (Web Text))

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Text #12

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Data Index: 626509 (C4 (Web Text))

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Text #13

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Data Index: 1000250 (C4 (Web Text))

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Text #14

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Text #15

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Max Act: 3.4539. Min Act: -0.1700

Data Index: 479267 (C4 (Web Text))

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Text #16

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Data Index: 1068394 (C4 (Web Text))

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Text #17

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Data Index: 1243074 (C4 (Web Text))

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Text #18

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Data Index: 1459027 (Python Code)

Max Activating Token Index: 1019

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Text #19

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Data Index: 990888 (C4 (Web Text))

Max Activating Token Index: 772

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