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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. 6-RES-JB
    6. 21082
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    Explanations

    quantitative data or measurements

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to quantification and analysis

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    HOME
    -0.80
     Mansion
    -0.72
    lihood
    -0.69
     blades
    -0.67
     spare
    -0.64
     Sutherland
    -0.63
     purse
    -0.60
     Papua
    -0.59
     pity
    -0.58
     Slayer
    -0.58
    POSITIVE LOGITS
    itatively
    1.64
    itative
    1.18
    ifiable
    1.17
    ifiers
    1.05
    idian
    1.04
    ifier
    1.03
    ifying
    1.02
    imet
    1.01
    ified
    1.01
     quant
    0.99
    Activations Density 0.025%

    No Known Activations