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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 5-RES-JB
    6. 12350
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    INDEX
    Explanations

    words related to military or violent actions, specifically the word "bombing"

    oai_token-act-pair · gpt-3.5-turbo

    references to bombing events or campaigns

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    laus
    -0.95
    eva
    -0.76
    Lear
    -0.75
    learn
    -0.75
    mia
    -0.74
    BOOK
    -0.74
    ITY
    -0.74
    mis
    -0.69
    Tang
    -0.69
    dit
    -0.68
    POSITIVE LOGITS
     bombing
    1.22
     bombings
    1.06
     raids
    1.03
     bomber
    0.97
     spree
    0.97
     barr
    0.94
     bombers
    0.91
     bombed
    0.86
     raid
    0.83
     bombard
    0.82
    Activations Density 0.017%

    No Known Activations