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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. 11-RES-JB
    11. 23072
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    Explanations

    phrases related to compensating for a loss or deficiency

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to compensation or making up for losses

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    onomy
    -0.90
    FTWARE
    -0.85
    bard
    -0.70
    20439
    -0.70
     answ
    -0.67
    chat
    -0.67
    1001
    -0.67
    archy
    -0.66
     Pastebin
    -0.65
    ierre
    -0.64
    POSITIVE LOGITS
     losses
    1.57
     lost
    1.23
     deficiencies
    1.23
     disadvantages
    1.19
     loss
    1.15
     shortfall
    1.14
     declines
    1.11
     shortcomings
    1.11
     damages
    1.10
     costs
    1.04
    Activations Density 0.232%

    No Known Activations