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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. 0-RES-JB
    11. 20049
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    Explanations

    adjectives that describe an evaluation or judgment, such as "complacent" and "ambitious"

    oai_token-act-pair · gpt-3.5-turbo

    variations of the word "adjacent" and related terms suggesting proximity or connection

    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
     Rouge
    -0.79
     rou
    -0.77
     whistle
    -0.68
     edited
    -0.67
     Flyers
    -0.66
     wel
    -0.65
     uninsured
    -0.64
     hacking
    -0.64
     impro
    -0.64
     pedals
    -0.63
    POSITIVE LOGITS
    acent
    2.75
    essential
    2.05
    endor
    1.28
     Mam
    1.09
    suff
    1.06
    enance
    1.02
    oken
    1.02
    Images
    1.00
    anqu
    0.98
    ainment
    0.94
    Activations Density 0.035%

    No Known Activations