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Dataset Setup

Finetuning Dataset

MBPP

python3 leti/scripts/data/process_mbpp.py \
    --output-dir data/processed/finetune/mbpp

Evaluation Dataset

HumanEval

# Note that human-eval is only for evaluation, but we still put it in the same folder.
python3 leti/scripts/data/process_humaneval.py \
    --output-dir data/processed/eval/humaneval

GSM8K (PaL prompt)

data/processed/raw/gsm8k-pal/gsm.jsonl can be downloaded from https://github.com/reasoning-machines/pal/blob/main/datasets/gsm.jsonl.

python3 leti/scripts/data/process_gsm8k_pal.py \
    --input-file data/processed/raw/gsm8k-pal/gsm.jsonl \
    --output-dir data/processed/eval/gsm

Big-Bench-Hard

mkdir external
git clone https://github.com/suzgunmirac/BIG-Bench-Hard.git
cd ..

python3 leti/scripts/data/process_bbh.py \
    --input-repo-dir external/BIG-Bench-Hard \
    --output-dir data/processed/eval/bbh

python3 leti/scripts/data/process_bbh.py \
    --input-repo-dir external/BIG-Bench-Hard \
    --output-dir data/processed/eval/bbh_cot \
    --cot

Event Argument Extraction

Following this repo to obtain eae-v6.4-train.jsonl and eae-v6.4-test.jsonl. We are not able to provide it directly due to copyright restriction of ACE-05.

PYTHONPATH=`pwd`:$PYTHONPATH python3 leti/scripts/data/process_eae.py \
    --train-file data/processed/raw/eae-v6.4-train.jsonl \
    --test-file data/processed/raw/eae-v6.4-test.jsonl \
    --output-dir data/processed/finetune/eae

Pre-training Dataset

python3 leti/scripts/data/process_the_stack.py \
    --gs_project $GCLOUD_PROJECT \
    --output-dir data/processed/pretrain/thestack-v1.1-50k

gsutil cp -r data/processed/pretrain/thestack-v1.1-50k $GS_BUCKET_PREFIX/data/processed/pretrain/thestack-v1.1-50k