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import os | |
from datasets import load_dataset, Dataset | |
TOKEN = os.environ.get("DEBUG") | |
requests_dataset = load_dataset("AIEnergyScore/requests_debug", split="test") | |
def normalize_task(task): | |
# Makes assumption about how the task names are being written, and called. | |
return '_'.join(task.split()).lower() | |
requests_dset = requests_dataset.to_pandas() | |
for model, task in requests_dset[['model', 'task']].loc[ | |
requests_dset['status'] == 'PENDING'].to_dict(orient='split', index=False)[ | |
'data']: | |
print("%s,%s" % (model, normalize_task(task))) | |