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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. 0-RES-JB
    11. 6277
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    Explanations

    the name "Ren" with varying activation strengths

    oai_token-act-pair · gpt-3.5-turbo

    mentions of the name "Ren" in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ibly
    -0.77
    ibles
    -0.76
    ible
    -0.76
    trak
    -0.74
    aves
    -0.69
     bombers
    -0.69
    alty
    -0.66
    Palest
    -0.65
     grind
    -0.65
    hots
    -0.63
    POSITIVE LOGITS
     Ren
    3.69
    Ren
    3.10
     ren
    1.56
     Nora
    1.44
     Reyn
    1.38
    ren
    1.36
     Jaune
    1.20
     Renault
    1.20
     Bren
    1.15
     Nicol
    1.15
    Activations Density 0.016%

    No Known Activations