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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
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    Explanations

    instances of people being caught in various situations

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "caught."

    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
     pronoun
    -0.80
    psey
    -0.71
     livest
    -0.71
     pronouns
    -0.69
    umably
    -0.67
    uras
    -0.67
    htar
    -0.65
     helicop
    -0.65
    arth
    -0.65
     agre
    -0.64
    POSITIVE LOGITS
    ãĤµ
    0.83
    ãĤ¤ãĥĪ
    0.80
    ãĤ¤
    0.78
    phrase
    0.73
     Tracks
    0.72
     Rai
    0.72
     caught
    0.72
    netflix
    0.71
    STDOUT
    0.69
     Trouble
    0.69
    Activations Density 0.013%

    No Known Activations