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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. 3173
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    INDEX
    Explanations

    common phrases related to academic, technical, and scientific topics, such as data analysis, classification, CPU specifications, and more

    oai_token-act-pair · gpt-3.5-turbo

    keywords associated with various social, cultural, and scientific themes

    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
    NEY
    -0.63
    aeda
    -0.59
     Sparks
    -0.56
    enegger
    -0.56
    sembly
    -0.55
    utterstock
    -0.55
    amins
    -0.55
    azo
    -0.53
     Godd
    -0.53
    bard
    -0.52
    POSITIVE LOGITS
    worthiness
    0.62
     coefficients
    0.61
     interpol
    0.60
     indices
    0.57
     expenditure
    0.56
     explanatory
    0.56
     vs
    0.53
     contexts
    0.53
    âĢIJ
    0.53
     Mathematics
    0.52
    Activations Density 1.229%

    No Known Activations