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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. 3-RES-JB
    11. 176
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    Explanations

    words related to theft or illegal acquisition, such as 'loot', 'looters', 'looting', and 'plunder'

    oai_token-act-pair · gpt-3.5-turbo

    terms related to theft and looting

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ioxide
    -0.69
    BRE
    -0.68
    cond
    -0.67
    Ther
    -0.65
    MAC
    -0.65
    66666666
    -0.65
    NULL
    -0.64
     Amateur
    -0.64
    Temperature
    -0.62
    PRES
    -0.62
    POSITIVE LOGITS
    ibrary
    1.04
     loot
    1.02
     looting
    0.96
     looted
    0.95
     piles
    0.83
     crates
    0.82
    fters
    0.81
    owship
    0.80
     Crate
    0.78
     carts
    0.74
    Activations Density 0.014%

    No Known Activations