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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. 9-RES-JB
    11. 13900
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    Explanations

    phrases that describe the impact or consequences of actions or events

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating significant effects or consequences

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    VERTISEMENT
    -0.84
    ça
    -0.76
    ahime
    -0.71
    ãĥĺ
    -0.70
    ativity
    -0.69
    earch
    -0.68
    wd
    -0.68
    ettings
    -0.67
    hower
    -0.67
    abin
    -0.67
    POSITIVE LOGITS
     slightest
    1.33
     wearer
    1.00
     greatest
    0.97
     same
    0.94
     likes
    0.93
     interviewer
    0.93
     impression
    0.93
     utmost
    0.93
     heaviest
    0.93
     opposite
    0.89
    Activations Density 0.279%

    No Known Activations