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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
    11. 13282
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    Explanations

    phrases relating to setting goals or targets

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to goals or intentions, particularly the term "sights."

    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
    gd
    -0.92
     Bahrain
    -0.72
    à¸
    -0.66
     entrusted
    -0.65
    lement
    -0.62
     chunk
    -0.62
     nond
    -0.61
     Success
    -0.60
     proportion
    -0.59
     Gupta
    -0.59
    POSITIVE LOGITS
     sights
    3.61
     traps
    0.98
    sight
    0.97
    alis
    0.96
     sails
    0.92
     landmarks
    0.90
    irie
    0.89
     attractions
    0.88
    ttes
    0.88
     Sight
    0.87
    Activations Density 0.028%

    No Known Activations