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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. 19933
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    Explanations

    participants in different studies or scenarios

    oai_token-act-pair · gpt-3.5-turbo

    references to study participants

    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
     Chop
    -0.63
     slic
    -0.62
    bia
    -0.61
     Bale
    -0.61
    Shock
    -0.61
    à¨
    -0.61
     Apocalypse
    -0.60
    bin
    -0.60
     Sabha
    -0.59
     à¨
    -0.58
    POSITIVE LOGITS
    hip
    0.96
    hips
    0.82
     who
    0.81
    cript
    0.78
    ele
    0.71
     sidx
    0.70
    ividual
    0.69
    erv
    0.67
     seated
    0.66
    imity
    0.66
    Activations Density 0.111%

    No Known Activations