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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. 16185
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    Explanations

    numbers related to statistics or measurements

    oai_token-act-pair · gpt-3.5-turbo

    numerical statistics related to sports performance

    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
    Not in Any Lists

    No Comments

    Negative Logits
    uana
    -0.68
    agine
    -0.64
    rella
    -0.63
    insula
    -0.62
    netflix
    -0.62
    actionDate
    -0.60
    onym
    -0.60
    rouse
    -0.60
    abi
    -0.58
    igm
    -0.58
    POSITIVE LOGITS
     consecutive
    1.03
     assists
    1.01
    %
    0.95
     interceptions
    0.94
     percent
    0.94
     outings
    0.91
     points
    0.90
     receptions
    0.90
     appearances
    0.88
    %,
    0.88
    Activations Density 0.121%

    No Known Activations