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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. 9-RES-JB
    11. 1654
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    Explanations

    mentions of high levels or amounts of something

    oai_token-act-pair · gpt-3.5-turbo

    references to elevated levels or quantities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    sov
    -0.86
    orio
    -0.80
    ranch
    -0.67
    vous
    -0.67
    \\\\\\\\
    -0.66
     Strait
    -0.66
    thood
    -0.64
    vice
    -0.64
    atio
    -0.64
    illance
    -0.63
    POSITIVE LOGITS
     enough
    1.12
     (>
    1.08
     (~
    0.86
     levels
    0.77
     overhead
    0.76
     compared
    0.76
    enough
    0.76
     (<
    0.76
     amounts
    0.73
     paced
    0.72
    Activations Density 0.082%

    No Known Activations