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{
  "model_type": "atome-lm",
  "architecture": "routed-ternary-3pathway",
  "_comment": "Atome LM is a custom architecture, NOT a transformers AutoModel. Load with atome_llm.core.atome_lm.AtomeLM from github.com/TilelliLab/atome-lm. This config documents the bundled checkpoints; it is not consumed by transformers.",

  "checkpoints": {
    "atome_944k.bin": {
      "format": "ATOME01 packed C-engine blob (4 trits/byte)",
      "precision": "ternary {-alpha, 0, +alpha} per tensor (BitNet b1.58 style)",
      "bits_per_weight": 1.58,
      "params": 944640,
      "disk_bytes": 276655,
      "loadable_by": "Atome C99 engine (atome_load)",
      "derived_from": "atome_1m_v1.pt"
    },
    "atome_1m_v1.pt": {
      "format": "PyTorch state_dict",
      "precision": "fp32 source (export to ternary via scripts/export_to_atome.py)",
      "params": 944640,
      "config": {
        "vocab_size": 256,
        "d_model": 256,
        "n_layers": 8,
        "d_head": 64,
        "top_k": 4,
        "kernel_size": 5,
        "n_pathways": 3
      },
      "tokenizer": "byte-level (no vocab file; ids 0-255)",
      "final_val_loss": 1.0545,
      "final_val_ppl": 2.87
    },
    "vanilla_1m_v1.pt": {
      "format": "PyTorch state_dict",
      "precision": "fp32",
      "role": "param-fair vanilla GPT baseline for the 944K reversal A/B in HONEST_RESULTS.md",
      "params": 950608,
      "config": {
        "kind": "vanilla_transformer_fp32",
        "vocab_size": 256,
        "d_model": 152,
        "n_layers": 3,
        "n_heads": 4,
        "d_ff": 608,
        "max_seq": 256
      },
      "final_val_loss": 0.9337,
      "final_val_ppl": 2.54
    }
  },

  "engine_default_config": {
    "_comment": "The C99 engine compile-time #defines; ~60K params, the MCU target regime (NOT the 944K bundled checkpoint).",
    "vocab_size": 256,
    "d_model": 64,
    "n_layers": 4,
    "d_head": 16,
    "top_k": 4,
    "kernel_size": 5,
    "n_pathways": 3
  },

  "training": {
    "corpus": "TinyStories (train.txt + valid.txt concatenated)",
    "steps": 30000,
    "seq_len": 256,
    "batch_size": 64,
    "accum_steps": 4,
    "optimizer": "AdamW lr 3e-4->3e-5 cosine, warmup 1000, weight_decay 0.1",
    "precision": "bf16 autocast",
    "seed": 0,
    "seeds_note": "single seed only; multi-seed variance not yet measured"
  },

  "license": "Apache-2.0",
  "version": "0.3.0",
  "source_repository": "https://github.com/TilelliLab/atome-lm",
  "project_home": "https://atomelm.com"
}