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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. 2779
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    Explanations

    quantitative data or numerical figures

    oai_token-act-pair · gpt-3.5-turbo

    references to numerical data related to counts and statistics

    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
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    No Comments

    Negative Logits
    cffffcc
    -0.87
    çīĪ
    -0.87
    ãĤ´ãĥ³
    -0.83
    arton
    -0.72
     guise
    -0.70
     sensibilities
    -0.67
     srfAttach
    -0.65
    haven
    -0.65
    ĺħ
    -0.65
    ĺ
    -0.63
    POSITIVE LOGITS
     per
    0.99
     counted
    0.96
     available
    0.93
     permissible
    0.88
     allowable
    0.87
     consumed
    0.84
     permitted
    0.82
     eligible
    0.81
     surveyed
    0.80
     allotted
    0.79
    Activations Density 0.313%

    No Known Activations