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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. 9-RES-JB
    11. 24136
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    Explanations

    phrases or words indicating specific intentions or goals

    oai_token-act-pair · gpt-3.5-turbo

    phrases that indicate intention or purpose

    oai_token-act-pair · gpt-4o-mini
    Triggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Negative Logits
    士
    -0.69
    ypes
    -0.68
    Optional
    -0.65
     Frie
    -0.63
    bugs
    -0.63
    ylon
    -0.62
    anon
    -0.61
     Ethiop
    -0.61
    animate
    -0.59
    oles
    -0.58
    POSITIVE LOGITS
     squarely
    1.20
     toward
    1.15
     towards
    1.14
     solely
    1.05
     specifically
    1.03
     principally
    0.98
     primarily
    0.98
     aimed
    0.89
     targeting
    0.88
     mainly
    0.88
    Activations Density 0.065%

    No Known Activations