config.json

{
  "model_name": "MMBench2 world model",
  "model_type": "dreamer4",
  "description": "Dreamer-4-style generative world model for large-scale multi-task continuous control, trained on the MMBench2 dataset (210 tasks). Accompanies the paper 'Hallucination in World Models is Predictable and Preventable'.",
  "paper": "https://www.nicklashansen.com/mmbench2",
  "dataset": "https://huggingface.co/datasets/nicklashansen/mmbench2",
  "total_params": 350000000,
  "observation": "224x224 RGB",
  "action_dim": 16,
  "num_tasks": 210,
  "components": {
    "tokenizer": {
      "params": 100000000,
      "file": "tokenizer.pt",
      "description": "causal video tokenizer (~50M encoder + ~50M decoder) with a 64-dim tanh-bounded latent"
    },
    "dynamics": {
      "params": 250000000,
      "file": "dynamics.pt",
      "description": "block-causal flow-matching Transformer with reward and behavior-cloning heads"
    }
  },
  "variants": {
    "base": "pretrained world model",
    "coverage_aware": "coverage-aware finetuned world model",
    "combined": "finetuned with all targeted data-collection sources"
  },
  "license": "mit"
}