Octo

Installation

Please clone the RoboVerse version of Octo and install the environment as required. We provide an official transform and configuration of RoboVerse fine-tuning setup there.

git clone https://github.com/wbjsamuel/RoboVerse-Octo.git

conda create -n octo python=3.10
conda activate octo
pip install -e .
pip install -r requirements.txt

Then, install jax based on your hardware settings. Here is an example for installing jax on a GPU machine with nvcc version 12.4:

pip install --upgrade "jax[cuda12_pip]==0.4.20" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
conda install -c nvidia cudnn=8.9

Data Preparation

For Octo, we still employ the RLDS-format data for fine-tuning. Please make sure your data have been successfully converted to RLDS format. If not, please refer to the OpenVLA documentation for related data conversion part. Then, all you need to do is just create a symbolic link of the converted RLDS data to the required path.

mkdir data
ln -s PATH_TO_RLDS_DATA data/YOUR_TASK_NAME

Finetune Octo

Launch your finetuning with finetune.sh:

export NCCL_IB_DISABLE=0
export NCCL_SOCKET_IFNAME=lo
export NCCL_DEBUG=INFO
export NCCL_NVLS_ENABLE=1

python scripts/finetune.py --config.pretrained_path=hf://rail-berkeley/octo-base