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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. 1-RES-JB
    11. 22800
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    Explanations

    comparative adjectives denoting positive characteristics such as 'sharper', 'smarter', 'brighter', and 'clearer'

    oai_token-act-pair · gpt-3.5-turbo

    adjectives that describe positive attributes or improvements

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    advertising
    -0.75
    Armor
    -0.72
    Ward
    -0.67
    ı
    -0.66
    Zone
    -0.66
     Station
    -0.62
    į
    -0.62
    EP
    -0.62
    mir
    -0.62
    Ox
    -0.62
    POSITIVE LOGITS
     than
    1.36
     Than
    1.23
    than
    1.15
     "$:/
    1.11
    anguage
    0.79
     millenn
    0.79
     proble
    0.78
     lapt
    0.76
    nces
    0.76
    odynam
    0.76
    Activations Density 0.020%

    No Known Activations