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
File size: 12,181 Bytes
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"title": "Qwen3-Omni Full-Parameter Feasibility Gates",
"generated_at_utc": "2026-06-18T12:53:13+00:00",
"status": "pass",
"decision": "full_parameter_feasible_for_guarded_short_runs_not_promoted",
"interpretation": "The full-parameter gates prove that Qwen3-Omni full-parameter FSDP can load, prepare, run backward/optimizer steps, and complete guarded pilots up to 256 optimizer steps on an 8-GPU remote worker. They do not prove a production full-parameter fine-tune, and they intentionally save no full checkpoints or public weights.",
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{
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"reason": "All completed full-parameter gate runs used save_mode=none; the preempted pilot saved nothing. These are feasibility evidence only."
},
"next_steps": [
"Keep the verified Qwen3-Omni LoRA adapter as the published production result for the 128-episode suite.",
"For a production full-parameter run, add a sharded checkpoint/resume plan before any long training launch.",
"Run a separate checkpointed full-parameter pilot only when GPUs are not needed by verified LoRA evaluation/publication work."
]
}
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