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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. 0-RES-JB
    6. 3307
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    Explanations

    mentions of the word "Sm" followed by either a numerical value of 9 or 10

    oai_token-act-pair · gpt-3.5-turbo

    mentions of the "Smoker" brand or related terminology

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ARCH
    -0.72
    orial
    -0.70
    aga
    -0.68
    bishop
    -0.66
    orus
    -0.65
     confir
    -0.64
    yrinth
    -0.63
    oire
    -0.63
     Cerberus
    -0.63
    agos
    -0.63
    POSITIVE LOGITS
     Sm
    3.68
    Sm
    2.54
    sm
    1.89
     sm
    1.60
     Smoke
    1.52
     SM
    1.44
     Smash
    1.38
     Smile
    1.37
     Smoking
    1.35
     Sn
    1.24
    Activations Density 0.020%

    No Known Activations