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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. 0-RES-JB
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    Explanations

    words related to placing importance or focus on certain subjects or concepts

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "emphasize" and its variations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     £
    -0.86
     neighbour
    -0.84
     Leeds
    -0.82
     Queensland
    -0.79
     mates
    -0.74
     neighbours
    -0.74
     Newcastle
    -0.73
     UK
    -0.72
     Belfast
    -0.72
     Cardiff
    -0.70
    POSITIVE LOGITS
     emphasized
    3.12
     emphasize
    2.94
     emphasizes
    2.77
     emphasizing
    2.51
     emphas
    2.08
     emphasis
    1.93
     undersc
    1.72
     underscore
    1.65
     stressed
    1.64
     stressing
    1.47
    Activations Density 0.019%

    No Known Activations