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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. 23247
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    Explanations

    phrases related to taking advantage of situations or opportunities

    oai_token-act-pair · gpt-3.5-turbo

    instances of exploitation or taking advantage of situations

    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
    cade
    -0.79
    kos
    -0.70
    gru
    -0.69
    arter
    -0.68
    ©¶æ
    -0.68
    enta
    -0.68
     dstg
    -0.67
    OTAL
    -0.66
    anners
    -0.66
    ħĭ
    -0.64
    POSITIVE LOGITS
     loopholes
    1.45
     opportunities
    1.24
     loophole
    1.23
     opportunity
    1.17
     weaknesses
    1.13
     vulnerabilities
    1.10
     strengths
    0.98
     weakness
    0.98
     favourable
    0.95
     vulnerability
    0.94
    Activations Density 0.178%

    No Known Activations