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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. 1114
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    Explanations

    phrases related to job skills and work environment

    oai_token-act-pair · gpt-3.5-turbo

    concepts related to economic conditions and business performance

    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
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    Negative Logits
    ieth
    -0.80
    asha
    -0.62
    brew
    -0.62
    itional
    -0.61
    Gaming
    -0.57
    tiny
    -0.57
    stream
    -0.56
    alle
    -0.56
    yss
    -0.55
    gro
    -0.55
    POSITIVE LOGITS
     (>
    0.73
     (<
    0.69
     imaginable
    0.69
     Draper
    0.69
     (.
    0.67
     ('
    0.66
    zzo
    0.63
     reperto
    0.63
     (âĪĴ
    0.62
    .","
    0.62
    Activations Density 0.765%

    No Known Activations