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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. 6-RES-JB
    11. 5551
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    INDEX
    Explanations

    terms related to financial income or earnings

    oai_token-act-pair · gpt-3.5-turbo

    references to financial profits and earnings

    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
    uran
    -0.76
    opol
    -0.73
     Lob
    -0.72
    sonian
    -0.71
    WARE
    -0.69
    creen
    -0.68
    otin
    -0.67
    ovie
    -0.64
     Wond
    -0.64
    OVA
    -0.63
    POSITIVE LOGITS
     streams
    1.06
     revenues
    0.92
     revenue
    0.90
     expenditure
    0.83
    atically
    0.81
     derived
    0.80
     shortfall
    0.80
     receipts
    0.80
     stream
    0.80
     redistributed
    0.76
    Activations Density 0.025%

    No Known Activations