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

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

Neuron 1564 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: 4.0470. Min Act: -0.1700

Data Index: 1561414 (Python Code)

Max Activating Token Index: 674

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Text #1

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Data Index: 1509414 (Python Code)

Max Activating Token Index: 441

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Max Act: 4.0157. Min Act: -0.1700

Data Index: 1591889 (Python Code)

Max Activating Token Index: 583

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Text #3

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Max Act: 4.0470. Min Act: -0.1700

Data Index: 254286 (C4 (Web Text))

Max Activating Token Index: 309

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Data Index: 1384560 (Python Code)

Max Activating Token Index: 954

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Data Index: 1410287 (Python Code)

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Data Index: 1423797 (Python Code)

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Data Index: 1407979 (Python Code)

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Text #8

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Data Index: 1634953 (Python Code)

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Text #9

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Data Index: 1435998 (Python Code)

Max Activating Token Index: 458

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Data Index: 1416792 (Python Code)

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Data Index: 1548897 (Python Code)

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Data Index: 1430765 (Python Code)

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Data Index: 1470000 (Python Code)

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Text #14

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Data Index: 1407158 (Python Code)

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Data Index: 1438529 (Python Code)

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Text #16

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Data Index: 1405556 (Python Code)

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Text #18

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Data Index: 1228615 (C4 (Web Text))

Max Activating Token Index: 920

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Text #19

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Data Index: 1439332 (Python Code)

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