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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. 2173
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    Explanations

    technical terms related to data and file manipulation

    oai_token-act-pair · gpt-3.5-turbo
    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
    CLASS
    -0.74
    mn
    -0.70
    rick
    -0.69
    Shot
    -0.68
    Thompson
    -0.64
    ERAL
    -0.61
    Hung
    -0.59
    ctor
    -0.59
    shed
    -0.58
    OUS
    -0.56
    POSITIVE LOGITS
     themselves
    1.21
     individually
    1.03
    selves
    0.98
     separately
    0.96
     consecut
    0.95
    heet
    0.94
     aloud
    0.94
    etting
    0.90
    creen
    0.89
     manually
    0.89
    Activations Density 0.502%

    No Known Activations