#!/usr/bin/env bash # Executed inside the HF Job container after the repo is cloned to /work. # Called by hf_run_space_train_job.sh bootstrap command. set -euo pipefail cd /work papermill --log-output --progress-bar --execution-timeout "${NB_EXEC_TIMEOUT}" \ training/train_grpo.ipynb training/train_grpo.executed.ipynb STAGE="/work/_run_upload" rm -rf "$STAGE" && mkdir -p "$STAGE/training" cp -a training/train_grpo.executed.ipynb "$STAGE/training/" [ -d plots ] && cp -a plots "$STAGE/" [ -d viraltest_trained_adapter ] && cp -a viraltest_trained_adapter "$STAGE/" if [ "${INCLUDE_CHECKPOINTS:-0}" = "1" ] && [ -d checkpoints ]; then cp -a checkpoints "$STAGE/" fi TARBALL="/tmp/r.tgz" ( cd "$STAGE" && tar -czf "$TARBALL" . ) export HOME=/tmp HF_HOME=/tmp/hf HUGGINGFACE_HUB_CACHE=/tmp/hfc HF_HUB_CACHE=/tmp/hfc TMPDIR=/tmp XDG_CACHE_HOME=/tmp mkdir -p "$HF_HOME" "$HF_HUB_CACHE" python3 -c " import os os.environ.setdefault('HOME', '/tmp') os.environ.setdefault('HF_HOME', '/tmp/hf') os.environ.setdefault('HUGGINGFACE_HUB_CACHE', '/tmp/hfc') os.environ.setdefault('HF_HUB_CACHE', '/tmp/hfc') os.environ.setdefault('TMPDIR', '/tmp') os.environ.setdefault('XDG_CACHE_HOME', '/tmp') from huggingface_hub import HfApi with open('/tmp/r.tgz', 'rb') as f: HfApi(token=os.environ.get('HF_TOKEN')).upload_file( path_or_fileobj=f, path_in_repo='run-output/artifacts.tar.gz', repo_id=os.environ['SPACE_REPO'], repo_type='space', ) print('Artifacts uploaded.') "