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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 4-RES-JB
    11. 19985
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    Explanations

    the word "squ" followed by different endings like "ashed," "iggles," "abbles," among others

    oai_token-act-pair · gpt-3.5-turbo

    the repetition of the substring "squ"

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

    No Comments

    Negative Logits
    geist
    -0.88
    tenance
    -0.75
     attribution
    -0.74
    WAYS
    -0.73
     dating
    -0.69
    OPLE
    -0.67
     Archdemon
    -0.67
    âĹ¼
    -0.67
     Killer
    -0.64
    ãĤ·ãĥ£
    -0.63
    POSITIVE LOGITS
    ishable
    1.14
    ount
    1.14
    irts
    1.08
    atted
    1.04
    ishers
    1.03
    alid
    1.01
    abb
    1.01
    ishy
    1.00
    ashed
    0.99
    ashing
    0.98
    Activations Density 0.008%

    No Known Activations