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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. 8-RES-JB
    11. 14153
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    Explanations

    references to regular occurrences or routines

    oai_token-act-pair · gpt-3.5-turbo

    references to routine or regularity

    oai_token-act-pair · gpt-4o-mini
    Triggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Negative Logits
    artisan
    -0.75
    lda
    -0.75
    ï¸ı
    -0.68
    kamp
    -0.68
    arta
    -0.68
    UST
    -0.67
    Sov
    -0.66
    Cub
    -0.66
    omer
    -0.63
    oms
    -0.62
    POSITIVE LOGITS
    ity
    1.21
     occurrence
    1.00
     intervals
    0.95
    cy
    0.95
    ization
    0.93
     ol
    0.92
    ised
    0.92
    izing
    0.91
    isation
    0.87
    ities
    0.86
    Activations Density 0.025%

    No Known Activations