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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. 3-RES-JB
    11. 23541
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    Explanations

    scientific terms or concepts related to research methodologies and study designs, particularly focusing on empirical and anecdotal evidence

    oai_token-act-pair · gpt-3.5-turbo

    references to empirical research and evidence

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    vous
    -0.73
    ebus
    -0.72
    hands
    -0.70
    VL
    -0.68
    NetMessage
    -0.67
    ways
    -0.67
    oles
    -0.67
    lain
    -0.65
    ittens
    -0.65
    say
    -0.64
    POSITIVE LOGITS
     empir
    0.97
     empirical
    0.91
    itatively
    0.87
    ãĥ¼ãĥĨãĤ£
    0.82
    wcsstore
    0.80
    ãĤº
    0.79
    odox
    0.78
     measurement
    0.77
     observation
    0.74
     evaluations
    0.73
    Activations Density 0.012%

    No Known Activations