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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. 9-RES-JB
    11. 1743
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    Explanations

    information related to offline activities and merits in a structured format

    oai_token-act-pair · gpt-3.5-turbo

    terms related to online activity and performance metrics

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
    anders
    -0.65
    nas
    -0.63
    raint
    -0.63
    ket
    -0.62
    Lens
    -0.62
    eu
    -0.62
     lobb
    -0.62
    ipers
    -0.61
    AU
    -0.60
    comb
    -0.60
    POSITIVE LOGITS
    ertodd
    0.88
    acters
    0.75
    romeda
    0.74
    Merit
    0.73
     WATCHED
    0.70
    sburgh
    0.69
    usercontent
    0.68
     COURT
    0.68
    risome
    0.68
    ¯¯¯¯¯¯¯¯
    0.67
    Activations Density 0.053%

    No Known Activations