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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. 2-RES-JB
    11. 7559
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    Explanations

    phrases related to the concept of "grain", which can be interpreted in various contexts such as agriculture, truth, or skepticism

    oai_token-act-pair · gpt-3.5-turbo

    references to the word "grain" in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    arios
    -0.73
     contemplated
    -0.70
    arre
    -0.69
    attled
    -0.69
    undai
    -0.68
     prosec
    -0.67
     battled
    -0.66
    joining
    -0.65
     waged
    -0.64
     Defenders
    -0.62
    POSITIVE LOGITS
    grain
    1.30
     Grain
    1.17
     grains
    1.16
     grain
    1.14
    aceutical
    0.89
     Foods
    0.80
    stocks
    0.74
    osate
    0.73
    kernel
    0.73
    weed
    0.73
    Activations Density 0.006%

    No Known Activations