# In-Context Imitation Learning via Next-Token Prediction by Max (Letian) Fu*, Huang Huang*, Gaurav Datta*, Lawrence Yunliang Chen, William Chung-Ho Panitch, Fangchen Liu, Hui Li, and Ken Goldberg at UC Berkeley and Autodesk (*equal contribution). [[Paper](https://icrt.dev/files/icrt.pdf)] | [[Project Page](https://icrt.dev/)] | [[Checkpoints](https://huggingface.co/mlfu7/ICRT)] | [[Dataset](https://huggingface.co/datasets/Ravenh97/ICRT-MT)] | [[Citation](#citation)] This repo contains the checkpoints for *In-Context Imitation Learning via Next-Token Prediction*. We investigate how to bring few-shot, in-context learning capability that exists in next-token prediction models (i.e. GPT) into real-robot imitation learning policies. In particular, we store the pre-trained vision encoder and ICRT model separately. Please find them in [encoder](crossmae_rtx/cross-mae-rtx-vitb.pth), [ICRT](icrt_vitb_droid_pretrained/icrt_vitb_droid_pretrained.pth), and [ICRT-Llama7B](icrt_llama7b_lora/icrt_llama7b_lora.pth). Please refer to the [code](https://github.com/Max-Fu/icrt) on installing the repo, training and inferencing the model. ## Dataset Structure ``` ICRT-MT ├── merged_data_part1.hdf5 │ ├── episode_1 │ │ ├── observation │ │ ├── exterior_image_1_left │ │ └── exterior_image_2_left │ │ └── wrist_image_left │ │ └── cartesian_position │ │ └── gripper_position │ │ └── joint_position │ │ ├── action │ │ ├── cartesian_velocity │ │ └── gripper_velocity │ │ └── joint_velocity │ │ └── cartesian_position │ │ └── gripper_position │ │ └── joint_position │ │ ├── language_instruction │ │ ├── language_instruction_2 │ │ ├── language_instruction_3 │ │ ├── language_embedding │ │ ├── language_embedding_2 │ │ ├── language_embedding_3 │ │ ... │ ├── episode_2 │ │ ... │ └── episode_3 │ ... └── merged_data_part1_keys.json ... ``` ## Citation Please give us a star 🌟 on Github to support us! Please cite our work if you find our work inspiring or use our code in your work: ``` @article{fu2024icrt, title={In-Context Imitation Learning via Next-Token Prediction}, author={Letian Fu and Huang Huang and Gaurav Datta and Lawrence Yunliang Chen and William Chung-Ho Panitch and Fangchen Liu and Hui Li and Ken Goldberg}, journal={arXiv preprint arXiv:2408.15980}, year={2024} } ```