{
  "model_name": "embeddinggemma-300m",
  "architecture": "gemma3-embedding",
  "tokenizer_repo": "google/embeddinggemma-300m",
  "parts": {
    "encoder": "encoder.mlpackage"
  },
  "io_contract": {
    "inputs": {
      "input_ids": {
        "shape": [
          1,
          128
        ],
        "dtype": "int32"
      },
      "attention_mask": {
        "shape": [
          1,
          128
        ],
        "dtype": "fp16",
        "doc": "1.0 for valid tokens, 0.0 for pad"
      }
    },
    "outputs": {
      "embedding": {
        "shape": [
          1,
          768
        ],
        "dtype": "fp16",
        "doc": "L2-normalized; Matryoshka-truncate the last dim"
      }
    }
  },
  "hidden_size": 768,
  "num_hidden_layers": 24,
  "num_attention_heads": 3,
  "num_key_value_heads": 1,
  "head_dim": 256,
  "intermediate_size": 1152,
  "vocab_size": 262144,
  "max_seq_len": 128,
  "sliding_window": 512,
  "sliding_window_pattern": 6,
  "layer_types": [
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "full_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "full_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "full_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention",
    "full_attention"
  ],
  "rms_norm_eps": 1e-06,
  "rope_theta_global": 1000000.0,
  "rope_theta_local": 10000.0,
  "embed_dim": 768,
  "dense_intermediate_dim": 3072,
  "pooling": "mean",
  "normalize": "l2",
  "matryoshka_dims": [
    768,
    512,
    256,
    128
  ],
  "task_prefixes": {
    "retrieval_query": "task: search result | query: ",
    "retrieval_document": "title: none | text: ",
    "classification": "task: classification | query: ",
    "clustering": "task: clustering | query: ",
    "similarity": "task: sentence similarity | query: ",
    "code_retrieval": "task: code retrieval | query: ",
    "question_answering": "task: question answering | query: ",
    "fact_verification": "task: fact checking | query: "
  },
  "quantization": "int8",
  "compute_units": "CPU_AND_NE"
}