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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    Explanations

    texts related to sports teams, specifically the Detroit Tigers

    oai_token-act-pair · gpt-3.5-turbo

    mentions of the Tigers, particularly in sports contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    uters
    -0.79
    idding
    -0.75
    aleigh
    -0.75
    trak
    -0.73
    Ïĥ
    -0.72
    ibel
    -0.70
    iture
    -0.69
    ITED
    -0.68
    utherford
    -0.68
    sth
    -0.67
    POSITIVE LOGITS
     Tigers
    1.35
     Tiger
    0.96
    emonium
    0.89
     tigers
    0.87
    opard
    0.79
     Pistons
    0.76
     tiger
    0.76
    igers
    0.75
     Lions
    0.75
    cano
    0.75
    Activations Density 0.008%

    No Known Activations