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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. 9-RES-JB
    11. 19925
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    Explanations

    mentions of sports teams

    oai_token-act-pair · gpt-3.5-turbo

    references to sports teams

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    dit
    -0.79
    tml
    -0.76
     drip
    -0.73
    grain
    -0.72
     Maw
    -0.71
    ranging
    -0.70
    sight
    -0.70
    pire
    -0.70
    tain
    -0.69
    tar
    -0.68
    POSITIVE LOGITS
    liquid
    0.95
     mates
    0.89
     captain
    0.85
     coached
    0.84
     rosters
    0.84
    mates
    0.82
    members
    0.81
    fights
    0.80
    ichick
    0.79
     mascot
    0.78
    Activations Density 0.075%

    No Known Activations