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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. 6-RES-JB
    11. 14923
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    Explanations

    terms related to specific things or people that draw attention or interest

    oai_token-act-pair · gpt-3.5-turbo

    terms related to attractions, particularly in tourism or interpersonal contexts

    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
    ordan
    -0.76
    krit
    -0.72
    roman
    -0.71
    uckles
    -0.70
    м
    -0.70
     PRESIDENT
    -0.69
    ardi
    -0.69
    20439
    -0.68
    erate
    -0.67
    igans
    -0.66
    POSITIVE LOGITS
     attraction
    1.27
     attractions
    1.08
     Flavoring
    0.81
     attracts
    0.71
     lure
    0.70
    rers
    0.70
    ĸļ
    0.69
    inson
    0.67
    pole
    0.67
     irresist
    0.65
    Activations Density 0.027%

    No Known Activations