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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. 5-RES-JB
    6. 16288
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    INDEX
    Explanations

    names with "hart" or "hardt"

    oai_token-act-pair · gpt-3.5-turbo

    references to specific leaders and their associated names

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    Magikarp
    -0.70
    URI
    -0.69
     millenn
    -0.68
    ntil
    -0.67
     veter
    -0.65
     tampering
    -0.65
     sclerosis
    -0.65
    pty
    -0.63
     corros
    -0.61
     sarc
    -0.60
    POSITIVE LOGITS
    hart
    0.97
    awi
    0.93
    ford
    0.85
    ãĤ¤ãĥĪ
    0.82
    enstein
    0.81
    hardt
    0.80
     Ducks
    0.79
    enberg
    0.76
    ilton
    0.75
     Jr
    0.73
    Activations Density 0.019%

    No Known Activations