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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. 2-RES-JB
    11. 12247
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    Explanations

    words related to things or places that draw attention or interest

    oai_token-act-pair · gpt-3.5-turbo

    terms related to attractions, particularly in the context of tourism and entertainment

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    stood
    -0.75
    glas
    -0.69
    м
    -0.68
    uckles
    -0.66
    nia
    -0.65
    Ñı
    -0.65
    ells
    -0.65
    DIT
    -0.63
    20439
    -0.63
    gans
    -0.63
    POSITIVE LOGITS
     attraction
    1.66
     attractions
    1.36
     Flavoring
    0.84
    ĸļ
    0.83
     lure
    0.79
    apore
    0.77
     attracts
    0.74
    rers
    0.74
     coerc
    0.70
     magnet
    0.69
    Activations Density 0.006%

    No Known Activations