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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. 1-RES-JB
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    Explanations

    terms related to financial revenue and income generation

    oai_token-act-pair · gpt-3.5-turbo

    references to revenue generation in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Lob
    -0.74
    ovie
    -0.68
    empl
    -0.66
    OVA
    -0.65
    uran
    -0.64
    imir
    -0.64
     Lead
    -0.63
    te
    -0.62
    ¯
    -0.61
    Sil
    -0.60
    POSITIVE LOGITS
     revenue
    1.23
     revenues
    1.19
    interstitial
    1.05
     Revenue
    1.01
     receipts
    0.98
     streams
    0.88
     expenditure
    0.86
     monet
    0.85
    atically
    0.82
     expenditures
    0.79
    Activations Density 0.009%

    No Known Activations