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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 5-RES-JB
    6. 19746
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    Explanations

    terms associated with attracting attention or interest

    oai_token-act-pair · gpt-3.5-turbo

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    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Oops
    -0.65
    chens
    -0.64
     surviving
    -0.63
     procedure
    -0.63
    hal
    -0.62
     Settlement
    -0.59
    ricia
    -0.59
     Factory
    -0.58
     Uz
    -0.57
    jab
    -0.57
    POSITIVE LOGITS
    entious
    0.89
     attract
    0.83
     attracts
    0.81
     attracted
    0.78
    interstitial
    0.76
    GGGGGGGG
    0.75
     attention
    0.73
    rament
    0.72
    dinand
    0.69
    glomer
    0.69
    Activations Density 0.024%

    No Known Activations