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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. 138
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    Explanations

    phrases related to evaluating the handling of situations or issues

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to the management or oversight of various situations or issues

    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
    hemat
    -0.74
    uni
    -0.73
    plex
    -0.69
    elong
    -0.69
    mare
    -0.65
    mpeg
    -0.65
    root
    -0.64
    inet
    -0.64
    zyme
    -0.63
    esis
    -0.62
    POSITIVE LOGITS
     mishand
    0.93
    bars
    0.92
     handling
    0.75
     handled
    0.75
    ahime
    0.75
    ttes
    0.74
     sensitive
    0.74
    tons
    0.71
    VICE
    0.67
    DAQ
    0.66
    Activations Density 0.024%

    No Known Activations