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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. 9092
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    Explanations

    mentions of people's names followed by either a positive or a negative sentiment in the context

    oai_token-act-pair · gpt-3.5-turbo

    sentence-ending punctuation

    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
    wcs
    -0.85
     unden
    -0.84
    arily
    -0.81
     livest
    -0.80
    anwhile
    -0.80
    ussion
    -0.78
    ãĤ´
    -0.75
    quartered
    -0.75
    aways
    -0.69
     coincide
    -0.68
    POSITIVE LOGITS
     Obama
    0.94
     Trump
    0.94
     Robot
    0.90
     Hyde
    0.87
     Bezos
    0.87
     Gandhi
    0.87
     Ack
    0.87
     Snowden
    0.86
     McMahon
    0.86
     Putin
    0.86
    Activations Density 0.042%

    No Known Activations