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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. 0-RES-JB
    11. 9397
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    Explanations

    mentions of earning income

    oai_token-act-pair · gpt-3.5-turbo

    mentions of income and earnings

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    iso
    -0.72
    ppo
    -0.69
    PD
    -0.66
    izes
    -0.65
    ctions
    -0.64
    olution
    -0.63
    wrapper
    -0.62
     DeL
    -0.62
     intervene
    -0.61
     References
    -0.59
    POSITIVE LOGITS
     earning
    3.41
     earn
    1.92
     earns
    1.69
     earned
    1.66
    Earn
    1.58
     earnings
    1.55
     earners
    1.43
     Earn
    1.42
    arning
    1.35
     achieving
    1.31
    Activations Density 0.007%

    No Known Activations