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 Evaluation
- Base model:
<workspace-parent>/modelscope_models/Qwen__Qwen3-Omni-30B-A3B-Instruct - Adapter:
<project>/checkpoints/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_lora/adapter_lora - Dataset:
<project>/results/omni_finetune/xperience10m_qwen3_omni_128ep_96train_16val_16test_valmon_20260605_dataset/dataset.jsonl - Eval split:
test - Samples:
448 - Episodes:
14 - Accuracy:
0.0246 - Macro-F1:
0.0027 - Unseen eval labels:
144
Artifacts include metrics.json, predictions.csv, per_class_metrics.csv, and confusion_matrix.csv.