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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. 7-RES-JB
    11. 5357
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    Explanations

    timestamps or time-related references

    oai_token-act-pair · gpt-3.5-turbo

    references to a specific point in time

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    avorite
    -0.83
    ortium
    -0.71
    warts
    -0.67
    allas
    -0.67
    ancial
    -0.65
    rosis
    -0.64
    ging
    -0.63
    raltar
    -0.63
     RAID
    -0.63
    andel
    -0.62
    POSITIVE LOGITS
    code
    0.75
    ZI
    0.74
    frames
    0.72
    codes
    0.70
    bell
    0.67
    isch
    0.63
     advertised
    0.63
     frame
    0.62
     Introduced
    0.59
    cens
    0.58
    Activations Density 0.034%

    No Known Activations