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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. 24007
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    Explanations

    quantitative expressions related to shooting accuracy in sports

    oai_token-act-pair · gpt-3.5-turbo

    numerical statistics and figures related to performance

    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
     because
    -0.60
    !,
    -0.59
    undrum
    -0.59
     indeed
    -0.55
     Originally
    -0.53
    adays
    -0.53
    ,[
    -0.53
    !!!
    -0.52
     definitely
    -0.50
    sectional
    -0.49
    POSITIVE LOGITS
    ׾
    0.52
    ãĤ´ãĥ³
    0.49
    dding
    0.49
    rared
    0.48
    Redd
    0.47
    nesota
    0.45
    bone
    0.45
    tu
    0.44
    ש
    0.44
    ocular
    0.44
    Activations Density 1.649%

    No Known Activations