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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. 7-RES-JB
    11. 219
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    Explanations

    the word "wan" with varying levels of intensity, potentially being related to a specific name or concept

    oai_token-act-pair · gpt-3.5-turbo

    the word "wan" and its variations in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ensed
    -0.73
    igslist
    -0.63
     defiance
    -0.63
    anwhile
    -0.63
     accur
    -0.62
     Mayhem
    -0.60
    andem
    -0.60
    aches
    -0.59
    ysis
    -0.58
    onial
    -0.58
    POSITIVE LOGITS
    igans
    1.07
     Kenobi
    0.96
    igan
    0.94
    hao
    0.93
    nee
    0.88
    loo
    0.86
    atche
    0.84
    athan
    0.84
    atar
    0.83
    ciating
    0.83
    Activations Density 0.026%

    No Known Activations