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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. 7-RES-JB
    11. 18958
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    Explanations

    numbers or quantifiers followed by time-related words or phrases

    oai_token-act-pair · gpt-3.5-turbo

    references to significant events or milestones

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    whatever
    -0.67
    jun
    -0.64
    medium
    -0.63
    ................................................................
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     debian
    -0.62
    bay
    -0.59
     ILCS
    -0.58
    00200000
    -0.58
     Defin
    -0.57
     Illusion
    -0.57
    POSITIVE LOGITS
     remotely
    0.89
    clusively
    0.77
     overtly
    0.73
     publicly
    0.70
    perty
    0.70
     anywhere
    0.67
    -+
    0.67
     ever
    0.66
     foray
    0.66
     officially
    0.64
    Activations Density 0.488%

    No Known Activations