Cloud GPU Training Environment Setup

Turn off the network proxy on your own computer

Otherwise the Jupyter command line may not open

Log in to the cloud GPU platform Featurize

https://featurize.cn?s=d7ce99f842414bfcaea5662a97581bd1

Join the user group and tell customer service that you are a fan of "Tongji Zihao" to claim a voucher

Launch a cloud GPU instance

Install and configure the environment

conda create -y -n lerobot python=3.12
conda activate lerobot
conda install ffmpeg=7.1.1 -c conda-forge -y
# git clone https://github.com/Seeed-Projects/lerobot.git ~/work/Lerobot
git clone https://github.com/huggingface/lerobot.git
cd lerobot
pip install -e ".[pi]"
pip install wandb --upgrade
# export HF_ENDPOINT=https://hf-mirror.com
hf auth login

Log in to wandb

wandb login
Copy and paste the API key, then press Enter

Mounting the dataset

Copy the instance download command, similar to:
featurize dataset download 7f40bdaa-b1a4-4c00-9652-ff26fd079109

unzip lerobot_zihao_dataset_shake_hands.zip

The dataset will appear under the ~ directory

Change the weight save frequency (optional)

Open lerobot/src/lerobot/configs/train.py

Change save_freq from 20_000 to 5_000

This way you can obtain a model weight file earlier in training