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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 9-RES-JB
    6. 72
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    Explanations

    phrases related to engraving and visual details, particularly on objects like shirts, balls, and coins

    oai_token-act-pair · gpt-3.5-turbo

    references to specific designs, images, or branding elements on clothing items

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    enough
    -0.85
    awatts
    -0.81
    ewitness
    -0.78
    inki
    -0.75
    tests
    -0.75
     allerg
    -0.75
     Limits
    -0.74
    Enough
    -0.73
    oxin
    -0.73
    íķ
    -0.73
    POSITIVE LOGITS
     logo
    1.28
     silhouette
    1.26
     embro
    1.23
     inscription
    1.22
     motif
    1.20
     clasp
    1.20
     emblem
    1.09
     caption
    1.08
     oval
    1.08
     draped
    1.05
    Activations Density 0.451%

    No Known Activations