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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

    words related to software, technology, and computing, particularly focusing on terms ending in "-ware"

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "ware," particularly in reference to various types of software and products

    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
     autonom
    -0.75
    unct
    -0.68
     plural
    -0.61
     Mane
    -0.61
    olar
    -0.61
    uations
    -0.60
    oresc
    -0.60
    uating
    -0.60
    ivas
    -0.60
    uation
    -0.59
    POSITIVE LOGITS
    ware
    1.33
    bytes
    1.07
    housing
    1.05
    ness
    1.00
    manship
    0.96
    WARE
    0.93
    fare
    0.91
    houses
    0.85
    cham
    0.84
    wana
    0.84
    Activations Density 0.015%

    No Known Activations