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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. 4-RES-JB
    11. 16646
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    Explanations

    calls to action prompting the reader to remember specific things or take specific actions

    oai_token-act-pair · gpt-3.5-turbo

    phrases emphasizing the importance of remembering or not forgetting something

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

    No Comments

    Negative Logits
    abase
    -0.81
    iHUD
    -0.81
    inals
    -0.75
    itte
    -0.74
    atform
    -0.69
    folk
    -0.69
    AMY
    -0.64
    Sphere
    -0.61
    gae
    -0.61
    é¾
    -0.61
    POSITIVE LOGITS
    theless
    0.99
    fulness
    0.76
    pieces
    0.70
    fully
    0.70
    ulously
    0.69
     Despair
    0.65
    phis
    0.65
     vividly
    0.64
    >)
    0.62
    ROR
    0.61
    Activations Density 0.012%

    No Known Activations