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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. 9-RES-JB
    6. 18744
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    Explanations

    mentions of various types of meetings and gatherings

    oai_token-act-pair · gpt-3.5-turbo

    references to formal meetings or conferences

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     depiction
    -0.72
     duplication
    -0.66
     cop
    -0.66
     guessed
    -0.65
     scanner
    -0.65
    aciously
    -0.65
     encaps
    -0.65
     churn
    -0.64
     gratification
    -0.64
     likeness
    -0.63
    POSITIVE LOGITS
     delegates
    1.10
     Presidents
    1.03
     lawmakers
    0.98
     senators
    0.98
     electors
    0.98
     MPs
    0.97
     governors
    0.96
     mayors
    0.95
     commissioners
    0.95
     chiefs
    0.94
    Activations Density 0.130%

    No Known Activations