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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. 2-RES-JB
    11. 14067
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    Explanations

    keywords related to feeding, such as "feeding", "feedstock", and "feed contamination"

    oai_token-act-pair · gpt-3.5-turbo

    references to feeding and food sources

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    vu
    -0.72
    itars
    -0.70
    alkyrie
    -0.68
    asar
    -0.65
    plets
    -0.61
    aspberry
    -0.60
    ESS
    -0.60
    ancouver
    -0.59
    illa
    -0.59
     boulder
    -0.59
    POSITIVE LOGITS
     feeds
    1.15
    feed
    1.13
     feed
    1.06
     Feed
    1.03
    stocks
    1.02
    parser
    0.95
    masters
    0.93
    Feed
    0.90
     fed
    0.89
    oras
    0.83
    Activations Density 0.009%

    No Known Activations