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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. 12540
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    Explanations

    phrases related to events and actions happening chronologically

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating the sequence of events or actions

    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
    .–
    -0.66
    ="/
    -0.66
     actionGroup
    -0.65
    ards
    -0.64
    osphere
    -0.63
    abal
    -0.62
    NAS
    -0.61
    ocracy
    -0.61
    ether
    -0.61
    ":"/
    -0.60
    POSITIVE LOGITS
    sequently
    1.00
    later
    0.84
    ward
    0.81
    sequent
    0.79
    Later
    0.79
     subsequent
    0.78
    ometime
    0.75
     thereafter
    0.75
    anwhile
    0.73
     later
    0.72
    Activations Density 0.324%

    No Known Activations