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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. 16014
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    Explanations

    phrases related to sports statistics, specifically focusing on scores, points, and game outcomes

    oai_token-act-pair · gpt-3.5-turbo

    punctuation marks, specifically commas

    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
    itarian
    -0.81
    onym
    -0.79
    izoph
    -0.78
    quartered
    -0.77
    izen
    -0.75
    ivan
    -0.75
    insula
    -0.71
    iless
    -0.69
    reprene
    -0.69
    è¦ļéĨĴ
    -0.68
    POSITIVE LOGITS
     finishing
    1.19
     scoring
    1.16
     averaging
    1.16
     completing
    1.02
    scoring
    1.00
     albeit
    1.00
     conced
    1.00
     totaling
    0.99
     earning
    0.95
     culminating
    0.95
    Activations Density 0.210%

    No Known Activations