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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. 3-RES-JB
    6. 21876
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    Explanations

    quotations inside double quotation marks

    oai_token-act-pair · gpt-3.5-turbo

    quoted speech

    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
     prelim
    -0.73
     livestream
    -0.68
     gossip
    -0.66
     filib
    -0.66
     clo
    -0.65
     mids
    -0.65
     spar
    -0.65
     footing
    -0.63
     est
    -0.62
     grades
    -0.62
    POSITIVE LOGITS
    We
    1.06
    Certainly
    0.97
    Our
    0.96
    It
    0.96
    Interest
    0.94
    Very
    0.93
    There
    0.93
    icious
    0.92
    They
    0.92
    I
    0.91
    Activations Density 0.105%

    No Known Activations