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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. 6930
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    Explanations

    names of individuals, particularly focusing on first names

    oai_token-act-pair · gpt-3.5-turbo

    names of people mentioned in the text

    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
     crosses
    -0.70
     paved
    -0.70
     rivalry
    -0.66
     triangle
    -0.64
     replaced
    -0.63
     collided
    -0.63
     jobs
    -0.63
     populated
    -0.62
     resembles
    -0.62
     shalt
    -0.61
    POSITIVE LOGITS
    rius
    0.76
    yna
    0.73
    Dispatch
    0.73
    kson
    0.73
    bart
    0.72
     Productions
    0.72
    kat
    0.70
    zon
    0.69
    zel
    0.69
    laus
    0.67
    Activations Density 0.440%

    No Known Activations