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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. 7794
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    Explanations

    phrases related to negative events or circumstances

    oai_token-act-pair · gpt-3.5-turbo

    colons followed by lists or explanations

    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
    roit
    -0.75
    Merit
    -0.69
    plex
    -0.69
    eware
    -0.67
    itarian
    -0.63
    icity
    -0.62
    ebin
    -0.61
    yon
    -0.61
    ities
    -0.60
    entle
    -0.60
    POSITIVE LOGITS
     namely
    1.10
     Provided
    0.95
     Firstly
    0.82
     Whereas
    0.78
     http
    0.78
    ↵Âł
    0.77
     "...
    0.77
     "'
    0.76
     "âĢ¦
    0.76
     https
    0.75
    Activations Density 0.113%

    No Known Activations