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
| # Reproducibility Contract | |
| This file defines what can be reproduced from the public repo and the official | |
| Xperience-10M sample, what each command should produce, and which results remain | |
| outside the current public data scope. | |
| ## Scope | |
| | Layer | Reproducible now | Current scope | | |
| | --- | --- | --- | | |
| | Sample download | Yes, from `ropedia-ai/xperience-10m-sample` or ModelScope sample mirror | Sample card lists `cc-by-nc-4.0`; raw data is not redistributed in this repo. | | |
| | Minimal baselines | Yes | One public sample episode, chronological split. | | |
| | 12-task suite | Yes | Uses the current 8,546-d synchronized multimodal feature contract. | | |
| | Neural MLP heads | Yes, when `torch` is installed | Compact task heads only, not a foundation model. | | |
| | Website figures and charts | Yes | Generated from committed metrics and sample thumbnails. | | |
| | Public bundle contents | Yes | Covers public repo and prepared HF bundles. | | |
| | Multi-episode Qwen3-Omni LoRA pilot | Not yet | Full-dataset access is granted; held-out metrics require completed staging, training, and evaluation. | | |
| ## Environment | |
| Use Python 3.12 when possible. The current public scripts depend on the HOMIE | |
| toolkit environment plus lightweight plotting and Hub tooling. | |
| ```bash | |
| git clone https://github.com/Ropedia/HOMIE-toolkit.git | |
| python3.12 -m venv .venv | |
| source .venv/bin/activate | |
| pip install -r HOMIE-toolkit/requirements.txt huggingface_hub hf_xet | |
| pip install -r ropedia-xperience-10m-task-suite/requirements.txt | |
| pip install torch | |
| ``` | |
| ## Data | |
| Download the public sample from Hugging Face: | |
| ```bash | |
| hf download ropedia-ai/xperience-10m-sample \ | |
| --repo-type dataset \ | |
| --local-dir data/sample/xperience-10m-sample | |
| ``` | |
| If Hugging Face access is unavailable in your environment, use the included | |
| ModelScope helper: | |
| ```bash | |
| python scripts/omni/download_sample_modelscope.py \ | |
| --output-dir data/sample/xperience-10m-sample \ | |
| --mode all-training | |
| ``` | |
| `--mode all-training` downloads `annotation.hdf5` and the six MP4 streams while | |
| skipping `visualization.rrd`. | |
| The sample card points to HOMIE Toolkit for inspecting videos and annotations. | |
| When `visualization.rrd` is downloaded for human inspection, open it with Rerun | |
| 0.29.0. The `.rrd` viewer artifact is not used by the training/evaluation | |
| scripts and is excluded from public publication bundles. | |
| ## Core Commands | |
| Run these from the repo root after setting `WORKSPACE` to the folder that owns | |
| `data/sample/xperience-10m-sample`. | |
| ```bash | |
| export WORKSPACE=/path/to/workspace | |
| python scripts/train_min_action_model.py --workspace "$WORKSPACE" | |
| python scripts/train_all_modalities_model.py --workspace "$WORKSPACE" | |
| python scripts/episode_task_suite.py \ | |
| --workspace "$WORKSPACE" \ | |
| --include-neural | |
| python scripts/research_direction_taxonomy.py | |
| python scripts/research_direction_extension_tasks.py | |
| python scripts/task_walkthroughs.py | |
| python scripts/validate_source_alignment.py | |
| python scripts/build_evaluation_protocol.py | |
| python scripts/generate_visualizations.py | |
| python scripts/render_overview_figures.py | |
| python scripts/render_task_suite_infographic.py | |
| python scripts/export_modality_atlas_assets.py | |
| python scripts/build_brand_assets.py | |
| python scripts/build_figure_index.py | |
| python scripts/validate_website_integrity.py | |
| python scripts/validate_task_surface.py | |
| python scripts/validate_scope_claims.py | |
| python scripts/build_artifact_index.py | |
| python scripts/validate_mirror_parity.py | |
| python scripts/validate_publication_package.py | |
| ``` | |
| ## Expected Public Outputs | |
| | Command group | Expected artifacts | | |
| | --- | --- | | |
| | Minimal baselines | `results/min_action_model/`, `results/min_all_modalities_action_model/`, metrics and model weights | | |
| | 12-task suite | `results/episode_task_suite/summary_report.json`, per-task `metrics.json`, predictions, confusion matrices | | |
| | Neural heads | `results/episode_task_suite/neural_mlp/**/metrics.json`, histories, model checkpoints | | |
| | Research directions | `results/episode_task_suite/research_directions/`, `docs/data/research_directions.json` | | |
| | Direction probes | `results/episode_task_suite/research_direction_extensions/`, `docs/data/research_direction_extensions.json` | | |
| | Walkthroughs | `results/episode_task_suite/task_walkthroughs/`, `docs/data/task_walkthroughs.json` | | |
| | Task surface integrity | `docs/data/task_surface_integrity.json` | | |
| | Source alignment | `SOURCE_ALIGNMENT_AUDIT.md`, `docs/data/source_alignment_audit.json` | | |
| | Evaluation protocol | `EVALUATION_PROTOCOL.md`, `docs/data/evaluation_protocol.json` | | |
| | Figures | `docs/assets/*.png`, `docs/assets/charts/*.svg` | | |
| | Brand assets | `docs/assets/brand/*.png`, `docs/favicon.png`, `docs/apple-touch-icon.png`, `docs/data/brand_assets.json` | | |
| | Figure index | `FIGURE_INDEX.md`, `docs/data/figure_index.json` | | |
| | Modality atlas | `docs/data/modality_atlas.json`, `docs/assets/modalities/*` | | |
| | Website integrity | `docs/data/website_integrity.json` | | |
| | Release reports | `docs/data/artifact_index.json`, `docs/data/mirror_parity.json`, `docs/data/publication_audit.json`, `docs/data/scope_claims_audit.json` | | |
| ## Exact-Match Reproduction Record | |
| The last full metric reproduction run was completed on **2026-05-30 | |
| Asia/Singapore** from a fresh output directory outside the repo. It rebuilt the | |
| minimal baselines, all-modality baselines, and the 12-task suite from the local | |
| public sample. The regenerated metrics matched the committed artifacts after | |
| float normalization. | |
| Evidence: | |
| - [`notes/reproducibility_audit.md`](notes/reproducibility_audit.md) | |
| - [`docs/data/reproducibility_matrix.json`](docs/data/reproducibility_matrix.json) | |
| ## Non-Reproducible From This Public Repo Alone | |
| The following require gated data, large model weights, or private compute | |
| state, so this repo does not yet provide public reproduction for: | |
| - a real held-out multi-episode Qwen3-Omni LoRA run, | |
| - held-out episode metrics for Qwen3-Omni, | |
| - full Xperience-10M-scale pretraining, | |
| - raw Xperience-10M video or annotation redistribution, | |
| - full Qwen weights or large full checkpoints. | |
| Before interpreting any Qwen3-Omni result, read | |
| [`docs/data/scope_claims_audit.json`](docs/data/scope_claims_audit.json), | |
| [`results/omni_finetune/DATA_ACCESS_STATUS.md`](results/omni_finetune/DATA_ACCESS_STATUS.md) | |
| and | |
| [`results/omni_finetune/MULTI_EPISODE_ACCESS_STATUS.md`](results/omni_finetune/MULTI_EPISODE_ACCESS_STATUS.md). | |