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

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

Neuron 1632 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: 3.5161. Min Act: -0.1700

Data Index: 1131585 (C4 (Web Text))

Max Activating Token Index: 580

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Text #1

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Max Act: 3.4063. Min Act: -0.1700

Data Index: 627436 (C4 (Web Text))

Max Activating Token Index: 109

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Text #2

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Max Act: 3.3436. Min Act: -0.1700

Data Index: 540157 (C4 (Web Text))

Max Activating Token Index: 247

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Text #3

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Max Act: 3.2965. Min Act: -0.1700

Data Index: 621094 (C4 (Web Text))

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Text #4

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Data Index: 121232 (C4 (Web Text))

Max Activating Token Index: 530

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Text #5

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Text #6

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Data Index: 961551 (C4 (Web Text))

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Text #7

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Text #8

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Data Index: 1321721 (C4 (Web Text))

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Text #9

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Data Index: 555978 (C4 (Web Text))

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Text #10

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Text #11

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Text #12

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Text #13

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Text #14

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Text #15

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Text #16

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Text #17

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Text #18

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Data Index: 41179 (C4 (Web Text))

Max Activating Token Index: 156

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Text #19

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Data Index: 1421099 (Python Code)

Max Activating Token Index: 678

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