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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. 11235
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    Explanations

    words related to public transportation, specifically mentioning "lin" which could likely be a reference to "subway," "metro," or another similar mode of transport

    oai_token-act-pair · gpt-3.5-turbo

    mentions of "lin" as a significant part of words, likely representing a specific entity or concept

    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
    Not in Any Lists

    No Comments

    Negative Logits
    awei
    -0.91
     Seym
    -0.82
    kward
    -0.78
    ansas
    -0.76
    illed
    -0.76
    dyl
    -0.72
    akening
    -0.71
    rences
    -0.68
    rely
    -0.67
    lance
    -0.66
    POSITIVE LOGITS
    ergic
    1.03
    eman
    0.97
     Rouge
    0.89
    fo
    0.86
    strument
    0.85
    ium
    0.84
    burg
    0.84
    emen
    0.83
    ergy
    0.81
    hurst
    0.81
    Activations Density 0.042%

    No Known Activations