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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 10-RES-JB
    6. 9859
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    Explanations

    dates from the late 1960s and early 1970s

    oai_token-act-pair · gpt-3.5-turbo

    references to specific years, particularly from the 1960s and early 1970s

    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
    venge
    -0.82
    EStreamFrame
    -0.69
    ndra
    -0.67
    erate
    -0.66
    hop
    -0.65
     explan
    -0.64
    plan
    -0.64
    uler
    -0.61
     lawy
    -0.61
    awed
    -0.60
    POSITIVE LOGITS
    -'
    0.85
    å¹
    0.80
     ILCS
    0.76
     BCE
    0.75
     onwards
    0.74
    çļ
    0.73
     Minutes
    0.71
     "$:/
    0.68
    oslov
    0.67
     onward
    0.66
    Activations Density 0.055%

    No Known Activations