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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. 10-RES-JB
    11. 20245
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    INDEX
    Explanations

    phrases emphasizing quantity or intensity

    oai_token-act-pair · gpt-3.5-turbo

    repetitive expressions of abundance or quantity

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    aves
    -0.85
    ares
    -0.84
    ħĭ
    -0.81
    save
    -0.78
    Ts
    -0.78
    adas
    -0.78
    ooters
    -0.78
    endars
    -0.77
    ãĥ¼ãĥ³
    -0.75
    opers
    -0.74
    POSITIVE LOGITS
     overlap
    1.20
     ambiguity
    1.15
     uncertainty
    1.14
     variability
    1.14
     disagreement
    1.12
     confusion
    1.11
     misinformation
    1.10
     evidence
    1.06
     animosity
    1.03
     speculation
    1.01
    Activations Density 0.135%

    No Known Activations