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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    Explanations

    the word "bulk"

    oai_token-act-pair · gpt-3.5-turbo

    discussion of large quantities or collections of items

    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
    iev
    -0.67
     Says
    -0.66
     Miy
    -0.63
    Park
    -0.62
    park
    -0.61
    Ã
    -0.60
    emi
    -0.60
     Ãī
    -0.60
    hatt
    -0.59
     Correct
    -0.59
    POSITIVE LOGITS
     bulk
    4.03
     Bulk
    1.96
    ulk
    1.45
     majority
    1.40
     brunt
    1.24
     bulky
    1.20
     vast
    1.11
     entirety
    1.11
     mass
    1.09
     remainder
    1.02
    Activations Density 0.014%

    No Known Activations