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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. 13304
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    Explanations

    phrases related to technology products or advancements

    oai_token-act-pair · gpt-3.5-turbo

    references to the market or availability of products and services

    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
     unaccompanied
    -0.74
     judgments
    -0.73
     beforehand
    -0.70
     aloud
    -0.68
     summ
    -0.67
     drafts
    -0.66
     according
    -0.65
     interpre
    -0.65
     because
    -0.65
     passages
    -0.65
    POSITIVE LOGITS
     same
    1.01
     market
    0.95
     marketplace
    0.92
     fray
    0.86
     internet
    0.86
     IoT
    0.86
     UK
    0.85
     enthusiast
    0.83
     forefront
    0.82
     Internet
    0.82
    Activations Density 0.378%

    No Known Activations