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    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. 8698
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    Explanations

    phrases marked with the abbreviation 'WH'

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of repeated or emphasized "WH" phrases and the term "Monitor."

    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
    opausal
    -0.64
     orbiting
    -0.64
     default
    -0.64
     shred
    -0.64
     racer
    -0.63
     bru
    -0.63
     fucking
    -0.62
     Rolls
    -0.62
     regression
    -0.61
     shuff
    -0.61
    POSITIVE LOGITS
    WH
    2.33
     Monitor
    1.65
    azar
    1.27
    itta
    1.11
    ritz
    0.99
    Screen
    0.96
    CHR
    0.94
    ACP
    0.94
    YA
    0.84
     Chambers
    0.81
    Activations Density 0.023%

    No Known Activations