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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. 10-RES-JB
    6. 13086
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    Explanations

    phrases indicating calls to action or suggestions for specific actions

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "call" in various forms, indicating demands or requests in the text

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    riks
    -0.62
     ILCS
    -0.61
    kus
    -0.59
    ãĥĹ
    -0.57
    mental
    -0.56
    ãĥ¼ãĥĨ
    -0.56
    女
    -0.56
    Ö¼
    -0.55
    é¾įå
    -0.55
    âĢ¢âĢ¢âĢ¢âĢ¢
    -0.55
    POSITIVE LOGITS
     attention
    1.20
     for
    1.00
     forth
    0.92
     upon
    0.92
    ously
    0.91
    enance
    0.87
    phas
    0.81
     into
    0.81
     Attention
    0.80
     bullshit
    0.75
    Activations Density 0.054%

    No Known Activations