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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. 7-RES-JB
    11. 11115
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    Explanations

    words related to important or crucial elements, events, or entities

    oai_token-act-pair · gpt-3.5-turbo

    terms related to significance and critical elements in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ttle
    -0.80
    enko
    -0.80
    ften
    -0.79
    culus
    -0.77
    illation
    -0.73
    claimer
    -0.72
    gemony
    -0.71
    emi
    -0.70
    igon
    -0.70
     Mania
    -0.68
    POSITIVE LOGITS
     areas
    1.09
     portions
    1.09
     items
    1.06
     aspects
    1.04
     parts
    1.00
     sectors
    0.99
     segments
    0.99
     sections
    0.98
     tasks
    0.95
     components
    0.95
    Activations Density 0.246%

    No Known Activations