multilinguality_megatron/preprocess_data.sh

#!/bin/bash

dataset_json="/mnt/scratch-artemis/kshitij/oneB_experiment/new_data_wout_covost/combined/to_tokenize.jsonl"
dataset_bin="/mnt/scratch-artemis/kshitij/LLAMA/latest_megatron_codebase/spgi_vox_mls_text_1b"
vocab_file="/mnt/scratch-artemis/kshitij/LLAMA/Megatron_LLM/temp/new_tokenizer/tokenizer.model"
repo="/mnt/scratch-artemis/kshitij/LLAMA/latest_megatron_codebase/multilinguality_megatron"

# Parse command-line arguments
for arg in "$@"
do
    case $arg in
        --help)
        echo "Usage: ./script.sh [OPTIONS]"
        echo "Options:"
        echo "  --dataset_json=PATH    Path to dataset json."
        echo "  --dataset_bin=PATH     Path to save preprocessed data."
        echo "  --vocab_file=PATH      Path to tokenizer.model file of HF model to be trained."
        echo "  --repo=PATH            Path to repo."
        exit 0
        ;;
        --dataset_json=*)
        dataset_json="${arg#*=}"
        shift
        ;;
        --dataset_bin=*)
        dataset_bin="${arg#*=}"
        shift
        ;;
        --vocab_file=*)
        vocab_file="${arg#*=}"
        shift
        ;;
        --repo=*)
        repo="${arg#*=}"
        shift
        ;;
    esac
done

echo $repo
mkdir -p $dataset_bin
python $repo/tools/preprocess_data.py \
    --input=$dataset_json \
    --output_prefix=$dataset_bin/data \
    --tokenizer_type=SentencePieceTokenizer \
    --vocab_file=$vocab_file \
    --chunk_size=64 \
    --workers=64 \
    --append_eod \
    --vocab_extra_ids 5000