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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. 8-RES-JB
    11. 7241
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    Explanations

    phrases related to setting and achieving goals

    oai_token-act-pair · gpt-3.5-turbo

    instructions or guidelines for achieving specific outcomes

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    Others
    -0.70
     afterwards
    -0.70
     latter
    -0.65
     afterward
    -0.61
    sequently
    -0.60
     thereafter
    -0.58
     later
    -0.58
     accordingly
    -0.58
    Otherwise
    -0.57
    Later
    -0.57
    POSITIVE LOGITS
     Accessed
    0.55
     surveyed
    0.51
     Introduction
    0.50
     polled
    0.49
     vagina
    0.48
     START
    0.48
     Suppose
    0.48
     Prevent
    0.47
     Expect
    0.47
     NAME
    0.47
    Activations Density 1.254%

    No Known Activations