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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. 3872
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    Explanations

    keywords related to regulation, proposals, reports, accents, features, stimulus, policies, failures, mic, leftist frameworks, high-profile events, fights, crowds, competing studios, historical figures, protesters, gatherings, challenging species, moving individuals

    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
    catentry
    -0.69
    ?".
    -0.69
     Âł Âł
    -0.67
    ttp
    -0.63
    )</
    -0.60
     pc
    -0.59
     ³³
    -0.59
     english
    -0.58
    /?
    -0.58
    )\
    -0.57
    POSITIVE LOGITS
     chiefly
    0.98
     insofar
    0.96
     principally
    0.90
     because
    0.88
     precisely
    0.84
     acutely
    0.84
    —
    0.78
     primarily
    0.77
     —
    0.76
     partly
    0.76
    Activations Density 1.033%

    No Known Activations