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
| # Qwen3-Omni LoRA Training | |
| - Base model: `<workspace-parent>/modelscope_models/Qwen__Qwen3-Omni-30B-A3B-Instruct` | |
| - Dataset run: `xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605` | |
| - Training run: `xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_lora` | |
| - Checkpoint: `<project>/checkpoints/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_lora/adapter_lora` | |
| - Processes: `8` | |
| - Train samples: `2848` | |
| - Validation samples: `512` | |
| - Epochs: `1` | |
| - Global step: `356` | |
| - Train loss: `0.413046` | |
| - Validation loss: `0.033066` | |
| This is the validation-aware diagnostic run. Raw Xperience-10M files, base-model weights, and adapter weights are not committed to this repo. | |