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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    9. 0-RES-JB
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    INDEX
    Explanations

    instances of the word "making" followed by an action or activity

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "making" in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    orne
    -0.81
    wered
    -0.74
    isance
    -0.73
    icum
    -0.72
    ledged
    -0.67
    raph
    -0.67
    hered
    -0.67
    ifacts
    -0.66
    lated
    -0.62
    aughtered
    -0.62
    POSITIVE LOGITS
     making
    2.99
    making
    2.19
     Making
    2.12
    Making
    1.92
     creating
    1.87
     giving
    1.70
     producing
    1.67
     putting
    1.60
     bringing
    1.56
     ensuring
    1.55
    Activations Density 0.032%

    No Known Activations