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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. 11-RES-JB
    6. 4573
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    Explanations

    words related to progression, reaching a target, and achieving a goal

    oai_token-act-pair · gpt-3.5-turbo
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    soType
    -0.83
    oral
    -0.69
     sponsoring
    -0.62
    irection
    -0.60
     fostering
    -0.59
    voice
    -0.58
     advocacy
    -0.58
     Supporting
    -0.57
     prescribing
    -0.57
    chool
    -0.57
    POSITIVE LOGITS
     exhausted
    1.00
    Completed
    0.99
     finish
    0.99
     finished
    0.98
     succeeded
    0.94
     exhaustion
    0.92
     completes
    0.90
     succeed
    0.90
     completed
    0.90
     missed
    0.88
    Activations Density 0.448%

    No Known Activations