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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. 12763
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    Explanations

    terms related to organizations or entities, specifically focusing on security vulnerabilities, regulations, and trade activities

    oai_token-act-pair · gpt-3.5-turbo

    acronyms or abbreviations associated with organizations or reports

    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
     awoken
    -0.70
     halves
    -0.68
     tion
    -0.65
    nces
    -0.64
    heimer
    -0.64
    chers
    -0.62
    perse
    -0.61
    doors
    -0.60
     Ashton
    -0.59
    enegger
    -0.58
    POSITIVE LOGITS
    RM
    1.10
    TN
    1.05
    Bs
    1.05
    CV
    1.03
    AN
    1.00
    EB
    0.99
    BG
    0.99
    RF
    0.99
    MN
    0.99
    OE
    0.98
    Activations Density 0.098%

    No Known Activations