---
license: apache-2.0
tags:
- robotics
- rlinf
- reinforcement-learning
- embodied-ai
- lingbotvla
- robotwin
pipeline_tag: robotics
---

# RLinf-lingbotvla-click-bell-grpo

This is a LingbotVLA checkpoint post-trained with RLinf GRPO on the RoboTwin `click_bell` task.

The checkpoint has been merged into the pinned RoboTwin SFT base format, so it can be loaded directly as a LingbotVLA model directory. It does not require a separate `runner.ckpt_path` file for evaluation.

## Base Model

- Upstream base: [`robbyant/lingbot-vla-4b-posttrain-robotwin`](https://huggingface.co/robbyant/lingbot-vla-4b-posttrain-robotwin)
- Base revision: `3e0c7c476bde3daaac00f79f3741a292a299f60a`
- RL method: RLinf GRPO
- RoboTwin task: `click_bell`

## Result Summary

In our RoboTwin random evaluation, this RLinf-GRPO checkpoint performs better than the pinned RoboTwin SFT checkpoint on the corresponding `click_bell` task.

## Download

```bash
hf download RLinf/RLinf-lingbotvla-click-bell-grpo \
    --local-dir RLinf-lingbotvla-click-bell-grpo
```

## Evaluation in RLinf

Use the downloaded directory as both `actor.model.model_path` and `rollout.model.model_path`. Keep `tokenizer_path` pointing to a local Qwen2.5-VL-3B-Instruct directory.

```bash
python examples/embodiment/eval_embodied_agent.py \
    --config-path examples/embodiment/config \
    --config-name robotwin_click_bell_grpo_lingbotvla \
    runner.only_eval=True \
    actor.model.model_path=/path/to/RLinf-lingbotvla-click-bell-grpo \
    actor.model.tokenizer_path=/path/to/Qwen2.5-VL-3B-Instruct \
    actor.model.lingbotvla.config_path=/path/to/RLinf-lingbotvla-click-bell-grpo \
    rollout.model.model_path=/path/to/RLinf-lingbotvla-click-bell-grpo \
    rollout.model.tokenizer_path=/path/to/Qwen2.5-VL-3B-Instruct \
    rollout.model.lingbotvla.config_path=/path/to/RLinf-lingbotvla-click-bell-grpo
```

For large RoboTwin evaluations, set `env.eval.total_num_envs`, `env.eval.max_episode_steps`, and `env.eval.max_steps_per_rollout_epoch` according to the target protocol.

## Notes

This repository stores the merged LingbotVLA model weights only. RLinf wrapper-only tensors, such as value heads used during training, are not included.