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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. 6-RES-JB
    6. 5384
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    Explanations

    words related to financial and business concepts, such as 'sales growth', 'debt', and 'incentives'

    oai_token-act-pair · gpt-3.5-turbo

    terms related to specific measurements, quantities, or classifications

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ãĤ³
    -0.67
    Pur
    -0.59
    Īè
    -0.57
     Summon
    -0.56
     festive
    -0.55
    MAP
    -0.55
    Joy
    -0.54
    Su
    -0.54
    arch
    -0.54
    å§
    -0.53
    POSITIVE LOGITS
     alike
    0.90
     respectively
    0.90
    depending
    0.80
    ,,,,
    0.72
    essions
    0.69
    src
    0.66
    ingen
    0.66
    ovi
    0.66
    oti
    0.66
    raised
    0.62
    Activations Density 0.353%

    No Known Activations