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

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

Neuron 626 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: 4.7662. Min Act: -0.1700

Data Index: 1306953 (C4 (Web Text))

Max Activating Token Index: 19

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Text #1

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Max Act: 4.7350. Min Act: -0.1700

Data Index: 1025535 (C4 (Web Text))

Max Activating Token Index: 28

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Text #2

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Max Act: 4.7662. Min Act: -0.1700

Data Index: 724174 (C4 (Web Text))

Max Activating Token Index: 15

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Text #3

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Max Act: 4.7037. Min Act: -0.1700

Data Index: 1511897 (Python Code)

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Text #4

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Max Act: 4.6725. Min Act: -0.1700

Data Index: 759368 (C4 (Web Text))

Max Activating Token Index: 70

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Text #5

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Data Index: 962665 (C4 (Web Text))

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Text #6

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Data Index: 551372 (C4 (Web Text))

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Text #7

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Data Index: 810181 (C4 (Web Text))

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Text #8

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Data Index: 191022 (C4 (Web Text))

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Text #9

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Data Index: 1255443 (C4 (Web Text))

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Text #10

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Data Index: 1171431 (C4 (Web Text))

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Text #11

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Text #12

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Text #13

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Data Index: 305653 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 1419384 (Python Code)

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Text #16

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Text #17

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Data Index: 109014 (C4 (Web Text))

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Text #18

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Data Index: 135586 (C4 (Web Text))

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Text #19

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Data Index: 11004 (C4 (Web Text))

Max Activating Token Index: 34

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