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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. 7-RES-JB
    11. 9730
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    Explanations

    words related to business operations and metrics, specifically focusing on the concept of 'turnover' or 'churn'

    oai_token-act-pair · gpt-3.5-turbo

    terms related to turnover, churn, and performance metrics

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    liam
    -0.74
    ican
    -0.71
    astern
    -0.69
    illac
    -0.69
    PLIED
    -0.66
    agos
    -0.65
    bourg
    -0.65
    este
    -0.64
    elin
    -0.64
    hed
    -0.64
    POSITIVE LOGITS
     margin
    0.77
     margins
    0.72
    gomery
    0.61
     rates
    0.61
    -----
    0.60
    lust
    0.60
    Decre
    0.59
    SIGN
    0.59
     SHARES
    0.59
     turnover
    0.58
    Activations Density 0.052%

    No Known Activations