Catalogue data - A Python Scripts to prepare catalogue data

Overview

catalogue_data

Scripts to prepare catalogue data.

Setup

Clone this repo.

Install git-lfs: https://github.com/git-lfs/git-lfs/wiki/Installation

sudo apt-get install git-lfs
git lfs install

Install dependencies:

sudo apt-add-repository non-free
sudo apt-get update
sudo apt-get install unrar

Create virtual environment, activate it and install dependencies:

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Create User Access Token (with write access) at Hugging Face Hub: https://huggingface.co/settings/token and set environment variables in the .env file at the root directory:

HF_USERNAME=
   
    
HF_USER_ACCESS_TOKEN=
    
     
GIT_USER=
     
      
GIT_EMAIL=
      

      
     
    
   

Create metadata

To create dataset metadata (in file dataset_infos.json) run:

python create_metadata.py --repo <repo_id>

where you should replace , e.g. bigscience-catalogue-lm-data/lm_ca_viquiquad

Aggregate datasets

To create an aggregated dataset from multiple datasets, and save it as sharded JSON Lines GZIP files, run:

python aggregate_datasets.py --dataset_ratios_path <path_to_file_with_dataset_ratios> --save_path <dir_path_to_save_aggregated_dataset>

where you should replace:

  • path_to_file_with_dataset_ratios: path to JSON file containing a dict with dataset names (keys) and their ratio (values) between 0 and 1.
  • : directory path to save the aggregated dataset
Owner
BigScience Workshop
Research workshop on large language models - The Summer of Language Models 21
BigScience Workshop
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