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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. 20194
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    Explanations

    potential actions or missed opportunities, often expressed in the form of "could have"

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating potential actions or possibilities expressed with "could have" constructions

    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
    Mem
    -0.62
     Kis
    -0.61
     Quarterly
    -0.57
    osi
    -0.55
    bert
    -0.55
    DT
    -0.54
    iaz
    -0.54
    Os
    -0.54
    Mp
    -0.53
     Blitz
    -0.53
    POSITIVE LOGITS
     easily
    1.06
     gotten
    0.98
     avoided
    0.96
     been
    0.93
    ħĭ
    0.88
     benefited
    0.85
     conce
    0.84
     afforded
    0.82
    kered
    0.82
    been
    0.82
    Activations Density 0.039%

    No Known Activations