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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. 6-RES-JB
    11. 7078
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    Explanations

    phrases related to the concept of time being used or invested

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to the concept of time and resources being allocated or expended

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
     boarded
    -0.62
     haunt
    -0.61
    ĪĴ
    -0.61
    venge
    -0.60
     faint
    -0.59
     prevailed
    -0.59
     Drops
    -0.58
     sleeper
    -0.56
    fortunately
    -0.56
     haun
    -0.56
    POSITIVE LOGITS
     devoted
    0.89
    /$
    0.89
    .$
    0.79
    ._
    0.78
     (£
    0.75
    ··
    0.75
     spent
    0.74
     expended
    0.73
     @@
    0.72
     GDDR
    0.71
    Activations Density 0.278%

    No Known Activations