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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    9. 4-RES-JB
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    Explanations

    mentions of the word "Wolf" with varying activations, possibly from different contexts or names

    oai_token-act-pair · gpt-3.5-turbo

    references to the word "Wolf"

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

    No Comments

    Negative Logits
    bably
    -0.88
    pora
    -0.82
    nces
    -0.77
    acists
    -0.76
    ntil
    -0.76
    ursed
    -0.74
    acterial
    -0.74
    senal
    -0.73
     conflic
    -0.73
     unnecess
    -0.73
    POSITIVE LOGITS
    enstein
    1.26
    hound
    1.22
    sburg
    1.14
     Wolf
    1.13
    Wolf
    1.03
    pack
    1.02
     Wolves
    1.00
    ram
    0.97
    gang
    0.93
    owitz
    0.92
    Activations Density 0.009%

    No Known Activations