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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 9-RES-JB
    11. 9155
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    Explanations

    phrases related to consequences or implications over a long period of time

    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
    ional
    -0.71
    \'
    -0.68
    bert
    -0.67
    irds
    -0.62
    illon
    -0.62
    ometers
    -0.61
    ben
    -0.61
    LEASE
    -0.60
    nance
    -0.60
     wondered
    -0.60
    POSITIVE LOGITS
     midst
    1.43
     slightest
    1.31
     guise
    1.26
     meantime
    1.23
     absence
    1.15
     sense
    1.11
     context
    1.07
     aftermath
    1.04
     manner
    1.04
     eyes
    0.97
    Activations Density 0.246%

    No Known Activations