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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. 9-RES-JB
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    Explanations

    past actions or habits

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "used" indicating past habits or states

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    olulu
    -0.64
     Ascend
    -0.62
    ¯¯¯¯
    -0.61
    atform
    -0.61
    merce
    -0.60
    llah
    -0.59
    antle
    -0.59
    Installation
    -0.58
    owship
    -0.58
    uta
    -0.58
    POSITIVE LOGITS
    fully
    1.06
     sparing
    0.84
     condoms
    0.84
    FUL
    0.83
    fulness
    0.71
     to
    0.69
    ãĥ¼ãĥĨãĤ£
    0.67
    ful
    0.67
     steroids
    0.64
    ãĥĨ
    0.64
    Activations Density 0.072%

    No Known Activations