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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. 10373
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    Explanations

    events or experiences that the person remembers or recalls with a strong emotional or vivid memory

    oai_token-act-pair · gpt-3.5-turbo

    instances of remembering or recalling memories

    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
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    Negative Logits
    acies
    -0.87
    ormal
    -0.77
    olitical
    -0.77
    earable
    -0.74
    oit
    -0.74
    eware
    -0.73
    ahime
    -0.73
    ourage
    -0.73
    tan
    -0.72
    orem
    -0.72
    POSITIVE LOGITS
     vividly
    1.51
     seeing
    1.33
     encountering
    1.26
     waking
    1.25
     hearing
    1.23
     distinctly
    1.14
     noticing
    1.11
     watching
    1.10
     wondering
    1.08
     having
    1.07
    Activations Density 0.051%

    No Known Activations