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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. 8-RES-JB
    11. 22661
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    Explanations

    language related to working diligently or with significant effort

    oai_token-act-pair · gpt-3.5-turbo

    the emphasis on hard work and effort

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    DATA
    -0.68
     Canad
    -0.67
    resy
    -0.67
    DragonMagazine
    -0.67
    ICAN
    -0.67
    ARDIS
    -0.65
    obyl
    -0.63
    ãĥĺãĥ©
    -0.63
    ipment
    -0.61
    cend
    -0.60
    POSITIVE LOGITS
    itud
    1.02
     enough
    0.93
    entimes
    0.84
    enough
    0.80
    working
    0.79
    esley
    0.79
    balls
    0.76
    nesses
    0.76
     diligently
    0.73
    terday
    0.73
    Activations Density 0.028%

    No Known Activations