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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 9-RES-JB
    6. 754
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    Explanations

    dates written in a specific format - month and year separated by a comma

    oai_token-act-pair · gpt-3.5-turbo

    numerical sequences or identifiers

    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
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    Negative Logits
     exha
    -0.70
     Ging
    -0.65
     waivers
    -0.63
     NF
    -0.62
     Graves
    -0.61
     Fior
    -0.60
     DRAG
    -0.60
     assumptions
    -0.60
     consulting
    -0.59
     Kass
    -0.59
    POSITIVE LOGITS
    606
    0.97
    708
    0.95
    20439
    0.93
    211
    0.92
    chev
    0.92
    307
    0.91
    806
    0.91
    285
    0.91
    wm
    0.90
    309
    0.89
    Activations Density 0.102%

    No Known Activations