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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. 0-RES-JB
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    Explanations

    words related to achieving victory or success

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "winning."

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    addons
    -0.76
    bars
    -0.70
     Anon
    -0.66
    afety
    -0.66
    orage
    -0.64
    redits
    -0.64
     advis
    -0.64
    afe
    -0.63
    aft
    -0.61
    ache
    -0.60
    POSITIVE LOGITS
     winning
    3.49
     Winning
    2.66
    winning
    2.41
     winner
    2.05
     winners
    1.96
     win
    1.90
     losing
    1.86
     wins
    1.81
    winner
    1.73
     victorious
    1.66
    Activations Density 0.010%

    No Known Activations