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import wandb
from huggingface_hub import login
import warnings
warnings.filterwarnings("ignore")
import os
import sys
path = os.path.abspath(os.path.join(os.path.dirname(__file__)))
sys.path.insert(0, path)
from src.pipelines.training_pipeline import training_pipeline
from src.utils import parse_args
def main():
# Load argument parser
args = parse_args()
print(f"\033[92mLoaded argument parsers\033[00m")
# Load token ID
huggingface_hub_token = args.huggingface_hub_token
wandb_token = args.wandb_token
if wandb_token:
os.environ["WANDB_PROJECT"] = "nlp_project"
# Login to Huggingface Hub and WandB
login(token=huggingface_hub_token)
print("\033[92mSuccessful login to Huggingface Hub\033[00m")
wandb.login(key=wandb_token)
print("\033[92mSuccessful login to WandB\033[00m")
training_pipeline(args)
print("\033[92mFinish training pipeline\033[00m")
if __name__=='__main__':
main() |