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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. 7-RES-JB
    6. 10676
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    INDEX
    Explanations

    strong correlations between different elements or factors mentioned in the text

    oai_token-act-pair · gpt-3.5-turbo

    discussions or references to correlations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    anas
    -0.84
    hoff
    -0.80
    thur
    -0.78
    ahime
    -0.76
    bern
    -0.73
    arde
    -0.72
    udeb
    -0.72
    sw
    -0.71
     Citiz
    -0.69
    apo
    -0.69
    POSITIVE LOGITS
     coefficient
    1.25
     coefficients
    1.09
     correlate
    0.85
    nces
    0.79
    relation
    0.78
     correlation
    0.75
    ifer
    0.75
     correlates
    0.71
    SHIP
    0.70
    inated
    0.69
    Activations Density 0.039%

    No Known Activations