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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. 7-RES-JB
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    Explanations

    quantitative and analysis-related terms

    oai_token-act-pair · gpt-3.5-turbo

    terms related to quantitative analysis and measurement

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    HOME
    -0.87
     Mansion
    -0.67
     Archdemon
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     Castle
    -0.62
     Marcos
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     Spit
    -0.60
    lihood
    -0.60
     Julius
    -0.60
    Wan
    -0.59
    ————————
    -0.58
    POSITIVE LOGITS
    itatively
    1.52
    ifiable
    1.07
    itative
    1.04
    idian
    1.01
     quant
    0.94
    rill
    0.91
    ities
    0.91
    ified
    0.88
    ifiers
    0.87
    ifies
    0.87
    Activations Density 0.026%

    No Known Activations