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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. 2752
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    Explanations

    sports team names

    oai_token-act-pair · gpt-3.5-turbo

    references to specific 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
     exper
    -0.85
    ãĤ´
    -0.82
     volunt
    -0.75
     behavi
    -0.75
    nsic
    -0.74
    igm
    -0.74
    iosyncr
    -0.73
    ERT
    -0.73
    igmatic
    -0.73
    NetMessage
    -0.72
    POSITIVE LOGITS
     Cardinals
    1.62
     Panthers
    1.52
     Falcons
    1.51
     Tigers
    1.48
     Packers
    1.47
     Colts
    1.47
     Grizzlies
    1.46
     Clippers
    1.46
     Dodgers
    1.45
     Blackhawks
    1.44
    Activations Density 0.152%

    No Known Activations