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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. 10-RES-JB
    11. 5336
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    Explanations

    adjectives related to efficiency and timing

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to efficiency and measurement in processes

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    orsi
    -0.72
    irens
    -0.68
    izons
    -0.63
    rapnel
    -0.62
    wat
    -0.61
    abies
    -0.61
     Desire
    -0.60
    rek
    -0.59
    IDES
    -0.58
    ahi
    -0.58
    POSITIVE LOGITS
     manner
    2.00
     fashion
    1.58
     way
    1.50
     ways
    1.34
     vein
    1.18
     guise
    1.17
     context
    1.17
     direction
    1.13
     manners
    1.12
     hurry
    1.10
    Activations Density 0.246%

    No Known Activations