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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. 6-RES-JB
    6. 24187
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    Explanations

    quantitative references related to numbers

    oai_token-act-pair · gpt-3.5-turbo

    references to quantities or numerical values, particularly involving hundreds

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    obal
    -0.75
    HAM
    -0.66
     Indust
    -0.63
    evin
    -0.61
    opens
    -0.59
    ivity
    -0.59
    kamp
    -0.58
    estine
    -0.57
    beh
    -0.57
    ign
    -0.56
    POSITIVE LOGITS
     thousand
    1.30
    ousand
    1.11
     Thousand
    1.06
     dollars
    1.06
    ths
    1.00
     miles
    0.98
     metres
    0.97
     pounds
    0.94
     kilometers
    0.93
     eighty
    0.91
    Activations Density 0.033%

    No Known Activations