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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. 20656
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    Explanations

    strong emotional or impactful terms related to various contexts

    oai_token-act-pair · gpt-3.5-turbo

    references to statistical data and its implications

    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
    NetMessage
    -0.82
    entimes
    -0.75
    ãĤ¼ãĤ¦ãĤ¹
    -0.75
    Ă
    -0.74
    ãĤ¦ãĤ¹
    -0.74
    ġ
    -0.73
     RandomRedditor
    -0.73
    ü
    -0.73
    ÷
    -0.73
    Ě
    -0.73
    POSITIVE LOGITS
     afterwards
    0.68
     ITV
    0.63
    ,
    0.61
     Anyway
    0.61
     Fifa
    0.56
     Spielberg
    0.56
     though
    0.56
     because
    0.55
     later
    0.55
     Simon
    0.55
    Activations Density 1.274%

    No Known Activations