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.