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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. 4-RES-JB
    11. 23999
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    Explanations

    phrases related to football statistics, specifically catches and receptions

    oai_token-act-pair · gpt-3.5-turbo

    references to catches in sports statistics

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

    No Comments

    Negative Logits
    olar
    -0.76
     hem
    -0.75
     Borders
    -0.74
     hemisphere
    -0.71
    htar
    -0.69
    onym
    -0.69
     sclerosis
    -0.68
    hov
    -0.66
     palp
    -0.65
     administrator
    -0.64
    POSITIVE LOGITS
    aways
    0.93
     receptions
    0.92
     touchdowns
    0.83
    phrase
    0.81
     Logged
    0.81
     Tackle
    0.79
    é¾
    0.79
     touchdown
    0.78
    ãĤĮ
    0.76
    backs
    0.74
    Activations Density 0.020%

    No Known Activations