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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 9-RES-JB
    6. 1147
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    INDEX
    Explanations

    percentage values

    oai_token-act-pair · gpt-3.5-turbo

    numerical data related to 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
     Kafka
    -0.67
     Arabian
    -0.67
     dive
    -0.65
     Dickinson
    -0.65
     drama
    -0.63
     Zoro
    -0.63
     flirt
    -0.63
     deduction
    -0.62
     Illum
    -0.62
     theatrical
    -0.62
    POSITIVE LOGITS
    thirds
    1.47
    enough
    1.34
    years
    1.29
    months
    1.26
    percent
    1.21
    million
    1.18
    month
    1.17
    times
    1.14
    billion
    1.14
    year
    1.14
    Activations Density 0.120%

    No Known Activations