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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. 733
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    INDEX
    Explanations

    phrases expressing degrees of comparison ("too + adjective/adverb") followed by a high activation value indicating a strong match

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating a degree of difficulty or ease

    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
    ngth
    -0.69
    workshop
    -0.66
    monary
    -0.65
    nan
    -0.64
    è¦ļéĨĴ
    -0.64
    ERT
    -0.62
    igi
    -0.62
    éĹĺ
    -0.60
    craft
    -0.60
    pez
    -0.59
    POSITIVE LOGITS
     much
    0.89
     bothered
    0.85
     terribly
    0.85
     bad
    0.83
     diss
    0.81
     flashy
    0.80
     distracting
    0.79
     keen
    0.78
    imilar
    0.75
     thrilled
    0.75
    Activations Density 0.031%

    No Known Activations