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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 6-RES-JB
    6. 22457
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    Explanations

    words related to specific types of cheese

    oai_token-act-pair · gpt-3.5-turbo

    mentions of food items, particularly cheese and culinary references

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    inations
    -0.74
    grounds
    -0.72
    isphere
    -0.71
    istics
    -0.69
    falls
    -0.68
    inator
    -0.68
     [*]
    -0.68
    opian
    -0.68
    room
    -0.67
     Weinstein
    -0.67
    POSITIVE LOGITS
     cheese
    1.01
     tuna
    0.84
     Cheese
    0.81
     hamb
    0.74
     steak
    0.72
     seasoning
    0.71
     Beef
    0.70
     grilled
    0.67
     burgers
    0.66
    -+-+-+-+
    0.65
    Activations Density 0.088%

    No Known Activations