Robotics
PyTorch
Cosmos
xperience10m_task_baseline_suite
embodied-ai
multimodal
xperience-10m
baseline
evaluation
qwen3-omni
Instructions to use cy0307/ropedia-xperience-10m-task-baselines with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use cy0307/ropedia-xperience-10m-task-baselines with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| { | |
| "id": "cosmos3_super_reasoner", | |
| "display_name": "Cosmos3-Super Reasoner", | |
| "status": "implemented", | |
| "model_family": "Cosmos3 / physical-world foundation models", | |
| "default_model_id": "nv-community/Cosmos3-Super", | |
| "local_model_env": "COSMOS3_SUPER_MODEL_DIR", | |
| "dataset_contract": "xperience10m_episode_json_qa_v1", | |
| "training_objective": "zero_shot_structured_episode_understanding_json_qa_via_vllm_reasoner", | |
| "split_policy": { | |
| "unit": "episode", | |
| "default_counts": { | |
| "train": 96, | |
| "val": 16, | |
| "test": 16 | |
| }, | |
| "leakage_guard": "uses the same 96/16/16 selected episode split as the Qwen3-Omni LoRA branch; no Super weights are updated" | |
| }, | |
| "modalities": { | |
| "direct_inputs": [ | |
| "multi-camera rendered mosaic video", | |
| "language prompt and label options" | |
| ], | |
| "conditioning_inputs": [ | |
| "prompt-side task schema and episode/window metadata" | |
| ], | |
| "targets": [ | |
| "structured action/subtask/contact/transition/object JSON" | |
| ], | |
| "excluded_inputs": [ | |
| "visualization.rrd", | |
| "raw annotation HDF5", | |
| "audio in the current vLLM Reasoner path" | |
| ] | |
| }, | |
| "entrypoints": { | |
| "selection_manifest": "scripts/omni/build_selection_episode_manifest.py", | |
| "export": "scripts/omni/parallel_export_qwen3_omni_action_dataset.py", | |
| "neutral_index": "scripts/omni/export_model_neutral_window_index.py", | |
| "train": "", | |
| "eval": "scripts/omni/eval_cosmos3_super_reasoner.py", | |
| "launcher": "scripts/omni/run_cosmos3_super_reasoner_eval.sh", | |
| "validate": "scripts/omni/validate_omni_finetune_run.py" | |
| }, | |
| "primary_metrics": [ | |
| "json_validity_rate", | |
| "action_macro_f1", | |
| "subtask_accuracy", | |
| "transition_accuracy", | |
| "next_action_accuracy", | |
| "contact_accuracy", | |
| "object_micro_f1", | |
| "held_out_episode_count" | |
| ], | |
| "artifact_contract": { | |
| "checkpoint_gate": "base_weight_vllm_reasoner_setup_metadata", | |
| "required_eval_files": [ | |
| "metrics.json", | |
| "predictions.jsonl", | |
| "predictions.csv", | |
| "per_class_metrics.csv", | |
| "confusion_matrix.csv", | |
| "server_info.json", | |
| "RUN_REPORT.md" | |
| ], | |
| "required_training_files": [ | |
| "training_metadata.json", | |
| "progress.jsonl" | |
| ], | |
| "public_package_allowed": [ | |
| "metrics", | |
| "predictions", | |
| "confusion matrices", | |
| "run reports", | |
| "server/model setup metadata", | |
| "episode and dataset manifests", | |
| "validation summaries" | |
| ], | |
| "public_package_forbidden": [ | |
| "raw MP4", | |
| "annotation HDF5", | |
| "Rerun RRD", | |
| "base-model weights", | |
| "fine-tuned weights", | |
| "checkpoints", | |
| "large archives" | |
| ] | |
| }, | |
| "extension_requirements": [ | |
| "This branch evaluates staged Cosmos3-Super Reasoner base weights through vLLM on the 128-episode held-out JSON task; it does not fine-tune or release new Cosmos weights.", | |
| "Create a separate Cosmos3-Super adapter/model repository only after a real fine-tuning run produces new adapter or checkpoint weights.", | |
| "Keep it separate from the Cosmos3-Nano future-window compatibility branch, which answers a different world-model retrieval target." | |
| ] | |
| } | |