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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. 9-RES-JB
    11. 8707
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    Explanations

    words related to understanding, analyzing, or learning processes

    oai_token-act-pair · gpt-3.5-turbo

    expressions of understanding or difficulty in understanding concepts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    requ
    -0.75
     contention
    -0.71
     ATK
    -0.68
     cancellation
    -0.66
     Rebell
    -0.65
     controversy
    -0.65
     contribut
    -0.65
     subsidy
    -0.65
    portation
    -0.63
    ammy
    -0.62
    POSITIVE LOGITS
     glean
    0.88
     aloud
    0.85
    »Ĵ
    0.84
     accurately
    0.82
     beforehand
    0.80
     firsthand
    0.78
    ographs
    0.77
     orally
    0.77
     decipher
    0.76
     subconscious
    0.76
    Activations Density 0.635%

    No Known Activations