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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. 4-RES-JB
    11. 16322
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    Explanations

    phrases related to negative consequences or destruction

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "ruin" and its variations

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

    No Comments

    Negative Logits
    leground
    -0.72
    bors
    -0.68
    appa
    -0.67
    arij
    -0.66
    heter
    -0.65
    States
    -0.63
    orney
    -0.63
    enne
    -0.62
    taboola
    -0.60
    duino
    -0.59
    POSITIVE LOGITS
     havoc
    1.08
    ous
    0.95
    ously
    0.91
     ruin
    0.90
     ruining
    0.87
    stal
    0.82
    iful
    0.81
     ruined
    0.81
     spoil
    0.81
    OUS
    0.80
    Activations Density 0.017%

    No Known Activations