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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. 0-RES-JB
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    Explanations

    adjectives describing predictability

    oai_token-act-pair · gpt-3.5-turbo

    references to predictability in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    umn
    -0.75
    aul
    -0.74
    TION
    -0.74
     enlarg
    -0.66
    iel
    -0.65
    adin
    -0.64
    anta
    -0.63
    yo
    -0.62
    craft
    -0.62
    asta
    -0.62
    POSITIVE LOGITS
     predictable
    3.73
     predictably
    1.89
     unpredictable
    1.73
     understandable
    1.33
     predetermined
    1.32
     Predict
    1.30
    redict
    1.26
     foreseeable
    1.24
     manageable
    1.23
     predict
    1.21
    Activations Density 0.025%

    No Known Activations