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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. 7-RES-JB
    11. 14384
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    Explanations

    words related to criminal activities or individuals involved in illegal activities

    oai_token-act-pair · gpt-3.5-turbo

    references to criminals and criminal activities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    Ħ¢
    -0.80
     increments
    -0.67
    arya
    -0.64
     Condition
    -0.62
     Herald
    -0.61
     NAD
    -0.61
    ollen
    -0.59
    ŃĶ
    -0.59
     Inspection
    -0.59
     Differences
    -0.59
    POSITIVE LOGITS
     prey
    0.91
     mastermind
    0.89
     gangs
    0.83
     who
    0.81
     smugg
    0.81
     whom
    0.79
     traff
    0.74
     addicted
    0.72
     stealing
    0.72
    ously
    0.72
    Activations Density 0.052%

    No Known Activations