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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. 8661
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    INDEX
    Explanations

    quantities or degrees of something, like "a lot" or "too much"

    oai_token-act-pair · gpt-3.5-turbo

    phrases that emphasize quantity or frequency

    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
     Niet
    -0.84
     horizont
    -0.70
    wr
    -0.68
    Mania
    -0.66
     exceeded
    -0.64
    DN
    -0.60
    thia
    -0.58
    anwhile
    -0.57
     Juda
    -0.57
     surrounded
    -0.56
    POSITIVE LOGITS
     mistake
    0.98
     noises
    0.97
     decisions
    0.97
     landfall
    0.95
     strides
    0.94
     assumptions
    0.92
     adjustments
    0.91
     mistakes
    0.90
     impression
    0.88
     pilgrimage
    0.88
    Activations Density 0.206%

    No Known Activations