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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. 17925
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    Explanations

    numbers related to quantities

    oai_token-act-pair · gpt-3.5-turbo

    numerical values and statistics in the text

    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
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    Negative Logits
    vati
    -0.64
     swearing
    -0.62
     counsel
    -0.61
     lod
    -0.60
     advertis
    -0.59
     sneaking
    -0.58
     eyel
    -0.56
     tender
    -0.56
     lodging
    -0.56
     ********************************
    -0.55
    POSITIVE LOGITS
    ½
    1.07
    nd
    0.96
    200
    0.92
     ½
    0.91
    800
    0.89
    Pac
    0.87
    %-
    0.85
    dfx
    0.84
    UP
    0.83
    Password
    0.83
    Activations Density 0.126%

    No Known Activations