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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. 9-RES-JB
    11. 24160
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    Explanations

    words related to food and beverages

    oai_token-act-pair · gpt-3.5-turbo

    nouns related to food, events, and physical items

    oai_token-act-pair · gpt-4o-mini
    Triggered 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
    Negative Logits
    \\\\\\\\
    -0.76
    Attempts
    -0.72
    ãĤ©
    -0.62
    abwe
    -0.60
     Ventures
    -0.59
    ilipp
    -0.59
    verified
    -0.58
    Press
    -0.57
    edIn
    -0.57
    utm
    -0.57
    POSITIVE LOGITS
     themselves
    1.31
    linger
    1.06
    cape
    0.99
    etter
    0.97
    mith
    0.92
    folk
    0.90
     aren
    0.90
    etting
    0.89
    pace
    0.89
    hest
    0.86
    Activations Density 0.484%

    No Known Activations