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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 6-RES-JB
    11. 14663
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    Explanations

    mentions of consuming a beverage, specifically drinking wine

    oai_token-act-pair · gpt-3.5-turbo

    references to drinking beverages, particularly alcohol

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.hook_resid_pre
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    24,576
    Data Type
    torch.float32
    Hook Point
    blocks.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    pora
    -0.72
    eele
    -0.72
    ural
    -0.71
    theless
    -0.70
    orp
    -0.70
    moving
    -0.68
     Sharif
    -0.66
    eq
    -0.65
    sure
    -0.64
    asia
    -0.63
    POSITIVE LOGITS
     bottles
    1.00
     alcohol
    0.96
     drinking
    0.96
    cohol
    0.91
     gallons
    0.91
     beverages
    0.90
     water
    0.89
     soda
    0.88
     Drink
    0.87
     glasses
    0.87
    Activations Density 0.020%

    No Known Activations