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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. 8128
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    Explanations

    settings or contexts involving technical specifications or instructions, such as shooting modes, camera details, and manual controls

    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
    tec
    -0.75
    rued
    -0.75
    bern
    -0.69
    obi
    -0.68
    arta
    -0.65
    cit
    -0.64
     Afric
    -0.63
    ãĥ¼ãĥ³
    -0.63
    iolet
    -0.63
    earth
    -0.63
    POSITIVE LOGITS
     treating
    1.38
     distributing
    1.35
     transferring
    1.35
     creating
    1.34
     owning
    1.33
     importing
    1.33
     stopping
    1.33
     putting
    1.31
     placing
    1.30
     reacting
    1.30
    Activations Density 0.336%

    No Known Activations