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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. 3586
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    Explanations

    phrases related to opinions or considerations of what is best or in the best interest

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to the best interests and options available in various contexts

    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
    pathy
    -0.70
     surplus
    -0.65
    actionDate
    -0.64
    ĸļ
    -0.62
    mut
    -0.61
    edu
    -0.60
    antom
    -0.59
    anced
    -0.59
    aos
    -0.59
    pathic
    -0.59
    POSITIVE LOGITS
     imaginable
    1.32
     EVER
    1.12
     ever
    0.99
    ever
    0.98
    Ever
    0.93
     Ever
    0.85
     shortest
    0.80
     conceivable
    0.76
    hest
    0.76
    rollers
    0.68
    Activations Density 0.680%

    No Known Activations