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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. 5-RES-JB
    6. 3634
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    Explanations

    references to a particular acronym "WR" followed by a numerical value

    oai_token-act-pair · gpt-3.5-turbo

    references to the 'WR' designation, likely indicating a specific type of character or item identifier in a context

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    anamo
    -0.80
     Maid
    -0.65
    uations
    -0.63
    omorphic
    -0.62
    onyms
    -0.59
     Crosby
    -0.58
     Belg
    -0.58
     Debor
    -0.57
    cles
    -0.57
    ovic
    -0.56
    POSITIVE LOGITS
    ONG
    1.18
    ACK
    1.08
    EST
    0.96
    MJ
    0.93
    IGHT
    0.90
    WR
    0.88
    IVES
    0.87
    ITT
    0.86
    ATH
    0.86
    IGHTS
    0.84
    Activations Density 0.009%

    No Known Activations