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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. 4-RES-JB
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    terms related to prediction and predictability

    oai_token-act-pair · gpt-3.5-turbo

    terms related to prediction and predictive analysis

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 4-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.4.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.4.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    4
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    dx
    -0.76
     Antiqu
    -0.74
    unal
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    untu
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    HOME
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    cca
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    ento
    -0.65
    undy
    -0.64
     Wine
    -0.63
     Ou
    -0.62
    POSITIVE LOGITS
     Predict
    1.05
     predict
    0.99
    itability
    0.96
    ively
    0.93
    ably
    0.91
    redict
    0.89
    ability
    0.87
     unpredict
    0.87
     predictive
    0.85
     probabilities
    0.83
    Activations Density 0.019%

    No Known Activations