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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. 6-RES-JB
    11. 4334
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    Explanations

    mentions of individuals who have been targeted or affected by negative events

    oai_token-act-pair · gpt-3.5-turbo

    references to victims in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    leaf
    -0.76
    REE
    -0.70
    yip
    -0.69
    CLASSIFIED
    -0.66
    ove
    -0.66
     Plat
    -0.64
    OPLE
    -0.63
     practicable
    -0.60
    andel
    -0.59
     unconventional
    -0.59
    POSITIVE LOGITS
    izes
    0.93
    izer
    0.92
    izers
    0.92
    vict
    0.92
    istics
    0.89
    Vict
    0.86
    ization
    0.86
     victim
    0.84
     Victim
    0.82
     victims
    0.78
    Activations Density 0.030%

    No Known Activations