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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. 12741
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    Explanations

    words related to training or being trained

    oai_token-act-pair · gpt-3.5-turbo

    references to training and preparation in various contexts

    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
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    Negative Logits
    FACE
    -0.73
     Meier
    -0.67
    adra
    -0.65
    ogene
    -0.64
    sm
    -0.62
    apest
    -0.62
    eu
    -0.61
    osi
    -0.61
    adr
    -0.60
    ãĥİ
    -0.60
    POSITIVE LOGITS
     instructors
    0.86
     certific
    0.79
     guiActiveUn
    0.75
     professionals
    0.75
     trained
    0.74
    arnaev
    0.73
    ĨĴ
    0.71
    dinand
    0.69
    icion
    0.68
     Swordsman
    0.68
    Activations Density 0.019%

    No Known Activations