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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. 3-RES-JB
    11. 20885
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    INDEX
    Explanations

    terms related to linear concepts, such as "linear narrative," "linear polarization," and "linear regression."

    oai_token-act-pair · gpt-3.5-turbo

    terms related to linearity and geometric concepts in structures or functions

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ardless
    -0.79
    flies
    -0.73
    UNE
    -0.73
    AMI
    -0.72
    Downloadha
    -0.71
     Pension
    -0.69
    aco
    -0.67
    avering
    -0.66
    raints
    -0.66
    earcher
    -0.66
    POSITIVE LOGITS
    ization
    1.03
    ized
    0.99
     algebra
    0.93
    ities
    0.91
    izes
    0.91
    izable
    0.88
    ity
    0.86
     interpol
    0.85
     accelerator
    0.80
     progression
    0.80
    Activations Density 0.014%

    No Known Activations