#DIR="/data/wet-data/output/toxic_filtered_without_bloom_new/2024-10/" | |
#TRAIN_DIR=$DIR | |
#OUTPUT_TRAIN_DIR="/data/hineng/data_multi/" | |
#DATASET_NAME="multi" | |
#FINAL_DIR="/data/datasets/$DATASET_NAME/" | |
#mkdir -p $FINAL_DIR $OUTPUT_TRAIN_DIR | |
#langs=($(ls -1 /data/wet-data/output/toxic_filtered_without_bloom_new/2024-10/ | awk '{split($0, a,"_"); print a[1]}' | uniq)) | |
#for lang in ${langs[@]}; do | |
# files=($(ls $TRAIN_DIR/$lang*)) | |
# OUTPUT_LANG_DIR=$OUTPUT_TRAIN_DIR/$lang | |
# FINAL_LANG_DIR=$FINAL_DIR/$lang | |
# mkdir -p $OUTPUT_LANG_DIR $FINAL_LANG_DIR | |
# for f in ${files[@]}; do | |
# new_name=$(echo $f | sed "s/\//_/g") | |
# cmd="unzstd $f --stdout > $OUTPUT_LANG_DIR/$(basename $f).jsonl" | |
# echo $cmd | |
# eval $cmd | |
# done; | |
#final_cmd="cat $OUTPUT_LANG_DIR/*.jsonl > $FINAL_LANG_DIR/final_en.jsonl" | |
#echo $final_cmd | |
#eval $final_cmd | |
#done; | |
FINAL_DIR=/data/datasets/hindi_english_arxiv_bengali/ | |
TOKENIZER=google/gemma-7b | |
TOKENIZER_TYPE=HuggingFaceTokenizer | |
#TOKENIZER=GPT2BPETokenizer | |
VOCAB_FILE= | |
MERGES_FILE= | |
ip_address=$(ifconfig | grep "inet " | grep -Fv "127.0.0.1" | grep -Fv "172.17.0.1" | awk '{print $2}') | |
mkdir -p $FINAL_DIR/tokenizer/ | |
filename=$(cat $FINAL_DIR/splitfile | grep $ip_address | awk '{print $1}') | |
cd /Model-References/PyTorch/nlp/DeepSpeedExamples/Megatron-DeepSpeed/ | |
python3 tools/preprocess_data.py \ | |
--input $FINAL_DIR/$filename \ | |
--output-prefix $FINAL_DIR/tokenizer/output_$ip_adress \ | |
--tokenizer_model_file $TOKENIZER \ | |
--dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\ | |
--append-eod --workers 8 #--chunk-size 50 | |
#--vocab-file $VOCAB_FILE \ | |
# --merge-file $MERGES_FILE \ | |