From ad964eb1b1c044d872978d7e016d59b6d44bff65 Mon Sep 17 00:00:00 2001 From: UniGen-X Date: Sun, 14 Sep 2025 23:08:33 +0800 Subject: [PATCH] Update README.md --- README.md | 16 ++++++++++++++-- 1 file changed, 14 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index d777ebf..121ca30 100644 --- a/README.md +++ b/README.md @@ -97,7 +97,19 @@ target_dir/ └── dataset1_name.csv ``` ## 🚴‍♂️ Training -To conduct training on a single or multiple datasets, please follow the steps below: +A. Our training strategy is outlined as follows: +- **Step 1**: Fine-tune a video generation model as the world model using the [Open-X](https://robotics-transformer-x.github.io/) dataset; +- **Step 2**: Post-train $\text{UnifoLM-WMA}$ in decision-making mode on the downstream task dataset; +
+ +
+- **Step 3**: Post-train $\text{UnifoLM-WMA}$ in simulation mode on the downstream task dataset. +
+ +
+**Note**: If you only require $\text{UnifoLM-WMA}$ to operate in a single mode, you may skip the corresponding step. + +B. To conduct training on a single or multiple datasets, please follow the steps below: - **Step 1**: The maximum DoF is assumed to be 16, if you have more than 16 DoF, update ```agent_state_dim``` and ```agent_action_dim``` in [configs/train/config.yaml](https://github.com/unitreerobotics/unifolm-wma/blob/working/configs/train/config.yaml) ; - **Step 2**: Set up the input shapes for each modality in [configs/train/meta.json](https://github.com/unitreerobotics/unitree-world-model/blob/main/configs/train/meta.json); - **Step 3**: Configure the training parameters in [configs/train/config.yaml](https://github.com/unitreerobotics/unitree-world-model/blob/main/configs/train/config.yaml). For the ```pretrained_checkpoint```, we recommend using the checkpoint " $\text{UnifoLM-WMA-0}_{Base}$ " fine-tuned on the [Open-X](https://robotics-transformer-x.github.io/) dataset; @@ -172,4 +184,4 @@ unitree-world-model/ ``` ## 🙏 Acknowledgement -Lots of code are inherieted from [DynamiCrafter](https://github.com/Doubiiu/DynamiCrafter), [Diffusion Policy](https://github.com/real-stanford/diffusion_policy) and [OpenVLA](https://github.com/openvla/openvla/tree/main). +Lots of code are inherieted from [DynamiCrafter](https://github.com/Doubiiu/DynamiCrafter), [Diffusion Policy](https://github.com/real-stanford/diffusion_policy) and [HPT](https://github.com/liruiw/HPT).