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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. 6-RES-JB
    11. 13792
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    Explanations

    terms related to sports players and their performances, particularly progress or achievements

    oai_token-act-pair · gpt-3.5-turbo

    references to sports and athletic achievements

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    RESULTS
    -0.60
    ".[
    -0.60
     attRot
    -0.58
     GOODMAN
    -0.57
     suscept
    -0.56
    "—
    -0.55
    âĶĢâĶĢâĶĢâĶĢâĶĢâĶĢâĶĢâĶĢ
    -0.54
    Ĥª
    -0.54
     Rowling
    -0.53
     exha
    -0.53
    POSITIVE LOGITS
     ..."
    0.68
    inav
    0.62
    idth
    0.61
     */
    0.60
     `
    0.57
     !!
    0.56
     {}
    0.56
     [-
    0.56
    )</
    0.56
     --------------------
    0.55
    Activations Density 2.161%

    No Known Activations