Instructions to use RLinf/LingBot-VLA-RoboTwin-EEF-ckpt1500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RLinf/LingBot-VLA-RoboTwin-EEF-ckpt1500 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RLinf/LingBot-VLA-RoboTwin-EEF-ckpt1500", device_map="auto") - Notebooks
- Google Colab
- Kaggle
LingBot-VLA RoboTwin EEF ckpt1500
This repository contains a LingBot-VLA checkpoint for RoboTwin EEF policy evaluation.
Contents
model-00001-of-00004.safetensorstomodel-00004-of-00004.safetensors: LingBot-VLA checkpoint shards.model.safetensors.index.json: checkpoint shard index.config.json: VLA model config.lingbotvla_cli.yaml: runtime config required by the LingBot-VLA loader.norm_stats/robotwin_eef.json: state/action normalization statistics.qwen_base/: local Qwen2.5-VL-3B-Instruct files used for config, tokenizer, processor, and base weights.
This repository does not include the RoboTwin simulator assets or the full LingBot-VLA source tree.
Usage
Download the repository:
from huggingface_hub import snapshot_download
model_dir = snapshot_download("RLinf/LingBot-VLA-RoboTwin-EEF-ckpt1500")
print(model_dir)
Start the LingBot-VLA policy server from a LingBot-VLA source checkout:
cd /path/to/VLA/code
QWEN25_PATH=<model_dir>/qwen_base \
CUDA_VISIBLE_DEVICES=0 \
OMP_NUM_THREADS=4 \
python -m deploy.lingbot_vla_policy \
--model_path <model_dir> \
--use_length 50 \
--port 8008 \
--norm_path <model_dir>/norm_stats/robotwin_eef.json
For RoboTwin hybrid evaluation, set the RoBoTwin-side VLA paths to the downloaded snapshot:
MODEL_PATH=<model_dir>
NORM_PATH=<model_dir>/norm_stats/robotwin_eef.json
QWEN25_PATH=<model_dir>/qwen_base
License Notes
The qwen_base/ directory contains Qwen2.5-VL-3B-Instruct materials. Qwen materials are distributed under the Qwen Research License. See qwen_base/LICENSE for the full license text.
This checkpoint is intended for research use.
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Model tree for RLinf/LingBot-VLA-RoboTwin-EEF-ckpt1500
Base model
Qwen/Qwen2.5-VL-3B-Instruct