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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. 2693
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    INDEX
    Explanations

    percentages expressed in the text

    oai_token-act-pair · gpt-3.5-turbo

    percentage figures, likely related to rarity or frequency metrics

    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
     lett
    -0.72
     compan
    -0.71
     brace
    -0.70
    redients
    -0.69
     accordingly
    -0.68
    iod
    -0.67
     directions
    -0.66
     punishment
    -0.65
     dwar
    -0.65
     shaped
    -0.65
    POSITIVE LOGITS
     Discuss
    0.97
    vantage
    0.75
     ----------------------------------------------------------------
    0.74
     Overall
    0.73
     Explosion
    0.71
     Avenger
    0.70
     Percent
    0.70
     ABV
    0.69
    ennial
    0.68
     Voice
    0.67
    Activations Density 0.044%

    No Known Activations