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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. 3-RES-JB
    11. 3088
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    Explanations

    the word "Quin" at varying activation strengths, possibly related to a specific individual or topic

    oai_token-act-pair · gpt-3.5-turbo

    proper nouns related to specific individuals and organizations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    utics
    -0.81
    ãĥī
    -0.78
    «ĺ
    -0.77
     eleph
    -0.76
    leeve
    -0.74
    Ļ½
    -0.73
    baugh
    -0.71
    ¦
    -0.70
    ographed
    -0.69
    ãĤ¢
    -0.69
    POSITIVE LOGITS
    naire
    1.00
    naires
    0.86
    Pont
    0.78
     Xuan
    0.78
     Fei
    0.74
    atche
    0.72
    selves
    0.72
     Qian
    0.71
    ified
    0.71
    Bridge
    0.70
    Activations Density 0.024%

    No Known Activations