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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 5-RES-JB
    6. 3141
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    phrases related to learning

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to education and the process of learning

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    abwe
    -0.75
    vati
    -0.67
    ordered
    -0.66
    lished
    -0.65
    berus
    -0.64
    conn
    -0.62
    raviolet
    -0.61
    idium
    -0.60
    zzi
    -0.59
    osi
    -0.58
    POSITIVE LOGITS
    learn
    0.93
    Lear
    0.87
    Learning
    0.82
    llor
    0.81
     Teach
    0.79
    shire
    0.77
    Learn
    0.77
     Lear
    0.75
     Curve
    0.74
    fulness
    0.74
    Activations Density 0.030%

    No Known Activations