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

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

Neuron 1113 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: 3.6429. Min Act: -0.1700

Data Index: 934419 (C4 (Web Text))

Max Activating Token Index: 491

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Text #1

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Max Act: 3.5802. Min Act: -0.1700

Data Index: 1093961 (C4 (Web Text))

Max Activating Token Index: 762

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Text #2

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Max Act: 3.6116. Min Act: -0.1698

Data Index: 1245211 (C4 (Web Text))

Max Activating Token Index: 236

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Text #3

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Max Act: 3.5489. Min Act: -0.1700

Data Index: 1383028 (Python Code)

Max Activating Token Index: 405

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Text #4

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Max Act: 3.4862. Min Act: -0.1694

Data Index: 1224256 (C4 (Web Text))

Max Activating Token Index: 772

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Text #5

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Data Index: 1098284 (C4 (Web Text))

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Text #6

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Data Index: 1020569 (C4 (Web Text))

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Text #7

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Data Index: 787391 (C4 (Web Text))

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Text #8

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Data Index: 10189 (C4 (Web Text))

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Text #9

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Data Index: 276420 (C4 (Web Text))

Max Activating Token Index: 483

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Text #10

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Data Index: 591295 (C4 (Web Text))

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Text #11

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Data Index: 600498 (C4 (Web Text))

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Text #12

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Data Index: 868810 (C4 (Web Text))

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Text #13

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Data Index: 1056092 (C4 (Web Text))

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Text #14

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Data Index: 1572017 (Python Code)

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Text #15

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Data Index: 50693 (C4 (Web Text))

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Text #16

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Text #17

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Data Index: 847471 (C4 (Web Text))

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Text #18

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Data Index: 707578 (C4 (Web Text))

Max Activating Token Index: 500

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Text #19

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Data Index: 1394942 (Python Code)

Max Activating Token Index: 225

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