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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 10-RES-JB
    6. 11771
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    Explanations

    sports teams or players, particularly focusing on football (NFL) and hockey (NHL)

    oai_token-act-pair · gpt-3.5-turbo

    proper nouns related to sports teams

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    utic
    -0.72
    vre
    -0.71
    tical
    -0.70
    quickShipAvailable
    -0.69
    oise
    -0.69
    ulence
    -0.67
    ancies
    -0.67
    iguous
    -0.66
    trak
    -0.65
    cemic
    -0.64
    POSITIVE LOGITS
     fans
    1.18
     Fans
    1.06
     coach
    1.02
     teammates
    0.98
     teammate
    0.98
     rookie
    0.97
    Fans
    0.95
    Nation
    0.95
     fan
    0.94
    Fan
    0.93
    Activations Density 0.077%

    No Known Activations