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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. 1-RES-JB
    11. 16085
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    Explanations

    proper nouns related to locations, specifically related to the term 'landers'

    oai_token-act-pair · gpt-3.5-turbo

    mentions of 'landers' and related terms in a context referring to sports or competitions

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    mits
    -0.69
    reon
    -0.66
     cumbers
    -0.65
    ramid
    -0.62
    odes
    -0.61
    ortion
    -0.61
     pse
    -0.60
    sa
    -0.60
    sis
    -0.60
    rices
    -0.59
    POSITIVE LOGITS
    lander
    1.21
    stown
    0.89
    DragonMagazine
    0.83
    ishly
    0.77
    imore
    0.77
    landers
    0.76
    gren
    0.70
    naire
    0.69
    witz
    0.69
    netflix
    0.68
    Activations Density 0.004%

    No Known Activations