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How to install Jiayi-Pan/TinyZero. Official installation instructions. Project installation guide. Framework or library installation. Build installation instructions. How to setup and install from GitHub. Installation steps and setup instructions. Official docs and installation instructions GitHub.

Jiayi-Pan/TinyZero Installation Guide

How to install Jiayi-Pan/TinyZero. Official project installation instructions and setup guide.

Automated Install (Recommended)

Quick installation instructions for Jiayi-Pan/TinyZero. This is the fastest way to complete project installation and setup.

Install via curl

curl -fsSL https://hexmos.com/ipm-install | bash && 
ipm i Jiayi-Pan/TinyZero
or

Install via npx

npx @hexmos/ipm i Jiayi-Pan/TinyZero

Prerequisites

Python

language

Version: 3.9.0

torch

package_manager

Version: 2.4.0

vllm

package_manager

Version: 0.6.3

ray

package_manager

Version: 1.2.0

veRL

system_tool

Version: vllm-specific-version

wandb

library

Version: 0.12.0

IPython

library

Version: 7.23.0

matplotlib

library

Version: 4.1.1

flash-attn

package_manager

Version: 0.5.4

conda

system_tool

Version: 4.13.0

Manual Installation Methods

Manual installation instructions. How to install from GitHub source.

Package Manager

conda create -n zero python=3.9

pip install torch==2.4.0 --index-url https://download.pytorch.org/whl/cu121

pip install vllm==0.6.3

pip3 install ray

verl

Script

conda activate zero

python ./examples/data_preprocess/countdown.py --local_dir {path_to_your_dataset} 

bash ./scripts/train_tiny_zero.sh

Shell Script

export N_GPUS=1

export BASE_MODEL={path_to_your_model}

export DATA_DIR={path_to_your_dataset}

export ROLLOUT_TP_SIZE=1

export EXPERIMENT_NAME=countdown-qwen2.5-0.5b

export VLLM_ATTENTION_BACKEND=XFORMERS

bash ./scripts/train_tiny_zero.sh

Shell Script

export N_GPUS=2

export BASE_MODEL={path_to_your_model}

export DATA_DIR={path_to_your_dataset}

export ROLLOUT_TP_SIZE=2

export EXPERIMENT_NAME=countdown-qwen2.5-3b

export VLLM_ATTENTION_BACKEND=XFORMERS

bash ./scripts/train_tiny_zero.sh

Shell Script

export N_GPUS=2

export BASE_MODEL={path_to_your_model}

export DATA_DIR={path_to_your_dataset}

export ROLLOUT_TP_SIZE=2

export EXPERIMENT_NAME=countdown-qwen2.5-3b-instruct

export VLLM_ATTENTION_BACKEND=XFORMERS

bash ./scripts/train_tiny_zero.sh

Post Installation Steps

  • Start the server using `python app.py`.
  • Run migrations with `python manage.py makemigrations && python manage.py migrate`