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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. 8814
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    Explanations

    references to sports-related phrases containing specific numbers associated with player positions or drafts

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the abbreviation "No." followed by a number

    oai_token-act-pair · gpt-4o-miniTriggered 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
    Not in Any Lists

    No Comments

    Negative Logits
    ãĥ¼ãĥĨ
    -0.73
     trave
    -0.65
     herds
    -0.63
    gypt
    -0.61
     disturbed
    -0.60
     lag
    -0.60
     otherwise
    -0.59
     pear
    -0.58
     interf
    -0.57
     traumatic
    -0.56
    POSITIVE LOGITS
    1
    0.65
     1
    0.63
    Ops
    0.62
    aucus
    0.62
    attr
    0.62
     Rider
    0.61
     Fool
    0.61
    brainer
    0.60
     Position
    0.60
    DIV
    0.60
    Activations Density 0.027%

    No Known Activations