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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. 10-RES-JB
    11. 8540
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    Explanations

    phrases indicating effort or attempt

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to effort and intention

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ELD
    -0.72
    zynski
    -0.70
    OPS
    -0.68
     Worse
    -0.66
    EStream
    -0.66
    UTH
    -0.63
    activation
    -0.62
     Liberation
    -0.60
    IFE
    -0.59
     Forced
    -0.57
    POSITIVE LOGITS
     minimize
    1.55
     avoid
    1.41
     ensure
    1.30
     minim
    1.24
    avoid
    1.21
     maintain
    1.21
     maximize
    1.18
     keep
    1.18
     adhere
    1.18
     emphasize
    1.15
    Activations Density 0.300%

    No Known Activations