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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. 3383
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    Explanations

    numeric values like percentages or counts

    oai_token-act-pair · gpt-3.5-turbo

    references to legal and financial matters

    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
    Interstitial
    -0.61
    interstitial
    -0.55
    Ń·
    -0.54
     pione
    -0.53
    TextColor
    -0.52
    onite
    -0.52
    ĥ
    -0.51
    Ķ
    -0.51
    emetery
    -0.50
    Ĭ
    -0.50
    POSITIVE LOGITS
     and
    0.76
     &
    0.67
     or
    0.62
     AND
    0.62
    <|endoftext|>
    0.61
    ,[
    0.59
    -,
    0.58
     ,
    0.55
    ,
    0.54
     nor
    0.53
    Activations Density 1.497%

    No Known Activations