Instructions to use arrow-hf/xvla-robotwin-place-empty-cup-300ep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use arrow-hf/xvla-robotwin-place-empty-cup-300ep with LeRobot:
- Notebooks
- Google Colab
- Kaggle
X-VLA RoboTwin place_empty_cup (300 ep, single instruction)
X-VLA policy fine-tuned on 300 demonstration episodes of the place_empty_cup task from RoboTwin 2.0 (demo_clean config), starting from the lerobot/xvla-base base checkpoint (Florence2 backbone, 879M params).
Training
| Config | Value |
|---|---|
| Base checkpoint | lerobot/xvla-base |
| Training data | 300 RoboTwin demonstrations, single instruction "place the empty cup" |
| Batch size | 32 |
| Steps | 20000 |
| dtype | bfloat16 |
| Optimizer | AdamW, lr=1e-4 |
| Chunk size | 32 |
Evaluation
RoboTwin 2.0 sim (demo_clean), 10 episodes, max_steps=400, action_chunk_exec=32.
Success rate: 7/10 (70%)
Usage
from lerobot.policies.xvla import XVLAPolicy
policy = XVLAPolicy.from_pretrained("arrow-hf/xvla-robotwin-place-empty-cup-300ep")
Important: Use action_chunk_exec=32 (full chunk). Default action_chunk_exec=16 causes 0% success on these tasks (TOPP replanning interference).
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Model tree for arrow-hf/xvla-robotwin-place-empty-cup-300ep
Base model
lerobot/xvla-base