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    Explanations

    the verb "have" used in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-att-kk
    Configuration
    ckkissane/attn-saes-gpt2-small-all-layers/gpt2-small_L5_Hcat_z_lr1.20e-03_l11.00e+00_ds49152_bs4096_dc1.00e-06_rsanthropic_rie25000_nr4_v9.pt
    Prompts (Dashboard)
    36,864 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    49,152
    Data Type
    float32
    Hook Name
    blocks.5.attn.hook_z
    Hook Layer
    5
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Head Attr Weights
    0:0.11
    1:0.13
    2:0.15
    3:0.03
    4:0.04
    5:0.15
    6:0.08
    7:0.03
    8:0.09
    9:0.03
    10:0.02
    11:0.09
    Negative Logits
    ulence
    -2.00
    vale
    -1.49
    ô
    -1.47
    kw
    -1.44
     Landing
    -1.41
    uper
    -1.39
    ingo
    -1.36
    ocity
    -1.36
    jas
    -1.36
    ozy
    -1.36
    POSITIVE LOGITS
     bothered
    1.57
     consulted
    1.56
     grading
    1.56
     satisfied
    1.56
    agree
    1.53
     touched
    1.52
     disapp
    1.51
     inclined
    1.48
     circumcised
    1.47
     disturbed
    1.45
    Activations Density 0.005%

    No Known Activations