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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. 6-RES-JB
    11. 7357
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    Explanations

    quantitative values related to statistics or data

    oai_token-act-pair · gpt-3.5-turbo

    the preposition "for" followed by numerical indicators or statistics

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    loo
    -0.84
    chenko
    -0.76
    hya
    -0.73
    mare
    -0.73
    iva
    -0.70
    iltr
    -0.69
    qqa
    -0.68
    moil
    -0.67
    athy
    -0.65
    Works
    -0.65
    POSITIVE LOGITS
    gery
    1.03
    bidden
    1.00
     purposes
    0.96
     comparison
    0.93
     example
    0.88
     instance
    0.86
    geries
    0.86
    aging
    0.86
     calculating
    0.80
    agers
    0.80
    Activations Density 0.173%

    No Known Activations