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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. 7-RES-JB
    11. 23019
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    Explanations

    adjectives describing the intensity or importance of specific attributes

    oai_token-act-pair · gpt-3.5-turbo

    adjectives and adverbs conveying strong negative or evaluative sentiments

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     DRAG
    -0.70
    azo
    -0.61
    asio
    -0.61
    ynski
    -0.60
    cision
    -0.57
     Flavoring
    -0.57
    adish
    -0.56
     Vaults
    -0.56
    omething
    -0.56
     BF
    -0.55
    POSITIVE LOGITS
    haus
    0.77
    accessible
    0.66
     unatt
    0.66
     ripe
    0.63
    rongh
    0.63
    hit
    0.61
    readable
    0.60
    vind
    0.60
    competitive
    0.60
     unsustainable
    0.59
    Activations Density 0.245%

    No Known Activations