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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. 10918
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    Explanations

    quantitative data or statistics presented in a visual format, like graphs or charts

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating statistical data and trends

    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
    ???
    -0.75
    tumblr
    -0.69
    nir
    -0.68
    Lago
    -0.67
    Engine
    -0.66
    bara
    -0.65
    venture
    -0.64
    thood
    -0.64
    another
    -0.64
    KER
    -0.64
    POSITIVE LOGITS
     approximate
    1.23
     entirety
    1.18
     number
    1.16
     amount
    1.15
     extent
    1.14
     entire
    1.14
     contents
    1.12
     percentage
    1.11
     probabilities
    1.10
     exact
    1.10
    Activations Density 0.281%

    No Known Activations