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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. 8-RES-JB
    11. 16799
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    INDEX
    Explanations

    words indicating goals or targets set by individuals or organizations

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to goals and targets, particularly in the context of achieving measurable outcomes

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    acted
    -0.88
    note
    -0.74
    guards
    -0.70
    mist
    -0.67
    mr
    -0.66
    actions
    -0.65
     Kush
    -0.64
    hot
    -0.64
    son
    -0.63
     palp
    -0.63
    POSITIVE LOGITS
     perfection
    0.98
     achieving
    0.96
     maximizing
    0.90
     2025
    0.90
     achieve
    0.88
     Achieve
    0.88
     improving
    0.84
     eradicate
    0.83
     completing
    0.82
     completion
    0.82
    Activations Density 0.229%

    No Known Activations