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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. 7-RES-JB
    6. 1400
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    INDEX
    Explanations

    the phrases or words indicating the result or outcome of a process or action

    oai_token-act-pair · gpt-3.5-turbo

    phrases that indicate causation or outcome

    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
    utical
    -0.90
    ppa
    -0.81
    quet
    -0.74
    Jar
    -0.71
    hazard
    -0.67
    mouth
    -0.67
    horn
    -0.66
    apo
    -0.66
    onyms
    -0.66
    iffe
    -0.65
    POSITIVE LOGITS
     sheer
    0.79
     inaction
    0.75
     combining
    0.70
     laz
    0.70
     subtract
    0.70
     having
    0.70
     absorbing
    0.69
     electing
    0.69
     being
    0.69
     removing
    0.67
    Activations Density 0.081%

    No Known Activations