Add model card with SEO metadata
Browse files
card.json
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{
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"model_type": "sparse-autoencoder",
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"base_model": "google/t5gemma-2-270m-270m",
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"architecture": "T5 Encoder-Decoder",
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"tasks": [
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"mechanistic-interpretability",
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"activation-steering",
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"feature-visualization",
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"model-interventions"
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],
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"languages": ["en"],
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"tags": [
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"sae",
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"sparse-autoencoder",
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"t5gemma",
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"t5gemma2",
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"google-t5gemma",
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"mechanistic-interpretability",
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"activation-steering",
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"steering",
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"feature-visualization",
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"neuronpedia",
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"gemma-scope",
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"sae-lens",
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"transformer-lens",
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"llm-interpretability",
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"explainable-ai",
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"xai",
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"model-steering",
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"feature-engineering",
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"representation-learning",
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"dictionary-learning",
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"layer-interpretation",
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"hidden-state-analysis",
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"nlp",
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"natural-language-processing",
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"text-to-text",
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"language-model",
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"llm",
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"large-language-model",
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"encoder-decoder",
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"transformer"
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],
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"datasets": [],
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"metrics": {
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"mse": 0.105,
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"cosine_similarity": 0.80,
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"l0_sparsity": 0.33,
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"final_loss": 0.0014
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},
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"training": {
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"epochs": 5,
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"batch_size": 2,
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"learning_rate": 0.0001,
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"optimizer": "AdamW",
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"l1_coefficient": 0.01,
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"d_sae": 4096,
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"d_in": 640
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}
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}
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