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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. 20435
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    Explanations

    words or phrases related to office settings or workplace scenarios

    oai_token-act-pair · gpt-3.5-turbo

    empty segments or breaks in the text

    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
    ¬¼
    -0.59
    iple
    -0.48
    ety
    -0.47
    natureconservancy
    -0.45
    izon
    -0.45
    odes
    -0.44
    ahu
    -0.42
     âĢķ
    -0.41
    reprene
    -0.41
    ":"/
    -0.40
    POSITIVE LOGITS
     albeit
    0.86
     namely
    0.82
     although
    0.78
     etc
    0.77
     however
    0.74
     respectively
    0.73
     though
    0.68
     aka
    0.68
     including
    0.66
     whereas
    0.66
    Activations Density 1.485%

    No Known Activations