Add config.json for download tracking

config.json

@@ -0,0 +1,82 @@
+{
+  "model_type": "cosmos-policy-planning",
+  "architecture": "diffusion-transformer",
+  "base_model": "nvidia/Cosmos-Policy-ALOHA-Predict2-2B",
+  "num_parameters": "2B",
+
+  "input_spec": {
+    "text": {
+      "type": "string",
+      "description": "Natural language task description"
+    },
+    "images": {
+      "format": "RGB",
+      "resolution": [224, 224],
+      "views": ["top_down", "left_wrist", "right_wrist"]
+    },
+    "proprioception": {
+      "dim": 14,
+      "components": ["left_arm_joints", "right_arm_joints"],
+      "joints_per_arm": 7
+    },
+    "actions": {
+      "dim": 14,
+      "horizon": 50,
+      "description": "Candidate action sequence to evaluate"
+    }
+  },
+
+  "output_spec": {
+    "future_proprioception": {
+      "dim": 14
+    },
+    "future_images": {
+      "resolution": [224, 224],
+      "views": 3
+    },
+    "value": {
+      "dim": 1,
+      "description": "Expected cumulative reward for action sequence"
+    }
+  },
+
+  "diffusion_config": {
+    "denoising_steps": 10,
+    "sigma_min": 4.0,
+    "sigma_max": 80.0
+  },
+
+  "planning_config": {
+    "ensemble_world_model_queries": 3,
+    "ensemble_value_queries": 5,
+    "total_predictions_per_action": 15,
+    "best_of_n_search": 8
+  },
+
+  "training": {
+    "dataset": "ALOHA policy rollouts",
+    "num_episodes": 648,
+    "hardware": "8x H100",
+    "batch_split": {
+      "policy": 0.1,
+      "world_model": 0.45,
+      "value_function": 0.45
+    }
+  },
+
+  "benchmark_results": {
+    "put_candies_in_bowl": 0.60,
+    "put_candy_in_ziploc_bag": 0.84,
+    "average": 0.72,
+    "improvement_over_base": 0.125
+  },
+
+  "inference": {
+    "precision": "bf16",
+    "latency_seconds": 4.9,
+    "recommended_gpus": 8
+  },
+
+  "robot_platform": "ALOHA 2 (ViperX 300 S dual arms)",
+  "control_frequency_hz": 25
+}