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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
    11. 1637
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    INDEX
    Explanations

    adjectives describing intensity or high degree

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "quite" used to emphasize qualities or characteristics

    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
    venant
    -0.93
     DRAG
    -0.84
    olan
    -0.80
    ults
    -0.79
    PLIED
    -0.76
    elsen
    -0.75
    selage
    -0.72
    igraph
    -0.72
    ulkan
    -0.71
    adium
    -0.70
    POSITIVE LOGITS
     frankly
    0.77
     nice
    0.75
     readable
    0.73
     enough
    0.73
     fitting
    0.72
     enjoyable
    0.70
     alright
    0.70
     unpleasant
    0.70
     amusing
    0.68
     impressive
    0.68
    Activations Density 0.014%

    No Known Activations