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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    7. Residual Stream
    9. 3-RES-JB
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    Explanations

    mentions of the word "escalator"

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "escal" and related terms in the context of startups and innovation

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    £ı
    -0.75
     depos
    -0.75
    ĨĴ
    -0.71
     electron
    -0.70
    hemy
    -0.67
     Checking
    -0.66
     Reck
    -0.66
    osate
    -0.65
     compiling
    -0.64
     spotting
    -0.63
    POSITIVE LOGITS
    ator
    1.13
    ators
    1.11
    ational
    1.05
    ows
    1.03
    atorial
    1.00
    atory
    0.92
    cer
    0.90
    imar
    0.90
    amus
    0.87
    inth
    0.86
    Activations Density 0.025%

    No Known Activations