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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. 10-RES-JB
    11. 5155
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    Explanations

    phrases related to decline or negative outcomes

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to decline or failure

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    phe
    -0.67
    ility
    -0.67
    ilege
    -0.65
    udence
    -0.65
    enance
    -0.63
    Applic
    -0.61
     Applic
    -0.61
    ile
    -0.59
    UAL
    -0.58
     anticipation
    -0.58
    POSITIVE LOGITS
     unnoticed
    0.98
    wagon
    0.78
     sidx
    0.77
    Ô
    0.72
    noticed
    0.71
    iral
    0.69
     undet
    0.68
     stairs
    0.68
    cycle
    0.68
    ribly
    0.67
    Activations Density 0.103%

    No Known Activations