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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. 3-RES-JB
    6. 19232
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    Explanations

    phrases related to things being of a low quality or level

    oai_token-act-pair · gpt-3.5-turbo

    references to low socioeconomic status or low quality

    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
    tnc
    -0.85
    andise
    -0.79
     Mahjong
    -0.75
    ophers
    -0.74
    itutional
    -0.71
     Orient
    -0.70
    thus
    -0.70
    cientious
    -0.69
     Pok
    -0.68
    arium
    -0.68
    POSITIVE LOGITS
     enough
    0.92
     pitched
    0.83
    est
    0.80
     hanging
    0.78
     dipping
    0.78
     priced
    0.76
     altitude
    0.74
     doses
    0.74
     ceilings
    0.73
     paced
    0.72
    Activations Density 0.028%

    No Known Activations