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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. 0-RES-JB
    11. 413
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    INDEX
    Explanations

    objects or concepts being brought together or unified

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "bringing"

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    heid
    -0.71
    geon
    -0.66
    arton
    -0.65
    opy
    -0.63
    ists
    -0.61
    oiler
    -0.61
    cit
    -0.58
    het
    -0.58
    ith
    -0.57
    hd
    -0.57
    POSITIVE LOGITS
     bringing
    2.98
    bringing
    2.38
     Bringing
    1.79
     introducing
    1.74
    Bring
    1.72
     delivering
    1.70
     bring
    1.65
     putting
    1.54
     attracting
    1.54
     providing
    1.53
    Activations Density 0.015%

    No Known Activations