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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. 7001
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    Explanations

    phrases related to specific actions or activities performed by individuals, such as driving, earning, walking, selecting, and spawning

    oai_token-act-pair · gpt-3.5-turbo

    terms related to participation and involvement of individuals or groups in activities

    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
    soType
    -1.12
    paren
    -0.82
     wounding
    -0.73
    traumatic
    -0.69
     tragic
    -0.68
    canon
    -0.67
     Dram
    -0.66
    FX
    -0.66
    quickShipAvailable
    -0.63
     Terrorism
    -0.63
    POSITIVE LOGITS
     spend
    1.10
     passively
    1.04
     roam
    0.96
     choose
    0.94
     spends
    0.94
     concentrate
    0.92
     starve
    0.90
     chooses
    0.90
     freely
    0.89
     autonom
    0.89
    Activations Density 0.648%

    No Known Activations