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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. 8551
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    Explanations

    phrases related to successful or impactful outcomes

    oai_token-act-pair · gpt-3.5-turbo

    phrases that emphasize hitting targets or achieving goals

    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
    fed
    -0.72
    ĨĴ
    -0.71
    SPONSORED
    -0.71
    shown
    -0.65
    spection
    -0.64
    erential
    -0.63
     steadfast
    -0.63
     ACTIONS
    -0.61
    pres
    -0.60
     Administ
    -0.60
    POSITIVE LOGITS
     stride
    0.90
     plateau
    0.78
    henko
    0.78
     snag
    0.76
    obin
    0.76
     iceberg
    0.73
    waves
    0.70
     lightning
    0.70
    ritic
    0.67
    geist
    0.67
    Activations Density 0.098%

    No Known Activations