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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 4-RES-JB
    6. 8663
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    INDEX
    Explanations

    statistically significant results within text

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating statistical significance and relationships in research findings

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

    No Comments

    Negative Logits
    dust
    -0.74
    roots
    -0.74
    wire
    -0.72
     commons
    -0.72
    lance
    -0.68
    åĤ
    -0.68
    din
    -0.67
    plates
    -0.66
    ä¸Ĭ
    -0.65
     vows
    -0.65
    POSITIVE LOGITS
     (âĪĴ
    1.13
     detectable
    1.04
     statistically
    1.00
     heterogeneity
    0.96
    RESULTS
    0.89
     comparing
    0.87
     correlated
    0.86
     correlation
    0.86
     correlate
    0.85
     correlations
    0.85
    Activations Density 0.142%

    No Known Activations