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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. 5-RES-JB
    6. 2891
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    INDEX
    Explanations

    words related to negative or problematic actions and descriptions

    oai_token-act-pair · gpt-3.5-turbo

    descriptors and traits associated with action movie characters and their archetypes

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    hower
    -0.69
    agements
    -0.57
     Repeat
    -0.57
     petitions
    -0.56
     Transcript
    -0.54
     Charges
    -0.53
    ploy
    -0.52
    usal
    -0.51
     absentee
    -0.50
    RESULTS
    -0.50
    POSITIVE LOGITS
    çͰ
    0.62
    ulhu
    0.61
    Õ
    0.59
    Ú
    0.58
    cients
    0.57
    Û
    0.55
    ãĥīãĥ©ãĤ´ãĥ³
    0.54
    Created
    0.53
     mascot
    0.53
     concept
    0.53
    Activations Density 2.483%

    No Known Activations