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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. 3-RES-JB
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    Explanations

    occurrences of the word "haha" at varying levels of emphasis

    oai_token-act-pair · gpt-3.5-turbo

    expressions of laughter or amusement

    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
    lining
    -0.90
    lines
    -0.78
    master
    -0.77
    parts
    -0.71
    ership
    -0.71
    picking
    -0.69
     directions
    -0.68
    writers
    -0.67
    writing
    -0.65
     direction
    -0.64
    POSITIVE LOGITS
    aha
    1.20
    ahah
    1.13
    qua
    0.95
    HAHA
    0.93
    ibaba
    0.93
    awk
    0.91
    UGH
    0.90
    ghan
    0.87
    apolis
    0.84
    ikk
    0.83
    Activations Density 0.008%

    No Known Activations