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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. 1-RES-JB
    11. 21443
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    INDEX
    Explanations

    mentions of shoplifting

    oai_token-act-pair · gpt-3.5-turbo

    terms related to lifting and weightlifting activities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    VA
    -0.71
    present
    -0.68
     RIS
    -0.66
     Palin
    -0.66
    ript
    -0.64
    ellen
    -0.63
     Mayo
    -0.62
     Waiting
    -0.62
     Senators
    -0.61
    displayText
    -0.61
    POSITIVE LOGITS
    lift
    1.12
    lifting
    1.06
    ifter
    0.94
    stakes
    0.87
     lifting
    0.86
    ifting
    0.86
    weight
    0.85
     advoc
    0.85
     weights
    0.83
     athlet
    0.82
    Activations Density 0.010%

    No Known Activations