EmbodiedAgentInterface/backend

1import os2 3from huggingface_hub import HfApi4 5# Info to change for your repository6# ----------------------------------7TOKEN = os.environ.get("HF_TOKEN") # A read/write token for your org8 9OWNER = "demo-leaderboard-backend" # Change to your org - don't forget to create a results and request dataset10 11# For harness evaluations12DEVICE = "cpu" # "cuda:0" if you add compute, for harness evaluations13LIMIT = 20 # !!!! For testing, should be None for actual evaluations!!!14NUM_FEWSHOT = 0 # Change with your few shot for the Harness evaluations15TASKS_HARNESS = ["anli_r1", "logiqa"]16 17# For lighteval evaluations18ACCELERATOR = "cpu"19REGION = "us-east-1"20VENDOR = "aws"21TASKS_LIGHTEVAL = "lighteval|anli:r1|0|0,lighteval|logiqa|0|0" 22# To add your own tasks, edit the custom file and launch it with `custom|myothertask|0|0``23 24# ---------------------------------------------------25REPO_ID = f"{OWNER}/backend"26QUEUE_REPO = f"{OWNER}/requests"27RESULTS_REPO = f"{OWNER}/results"28 29# If you setup a cache later, just change HF_HOME30CACHE_PATH=os.getenv("HF_HOME", ".")31 32# Local caches33EVAL_REQUESTS_PATH = os.path.join(CACHE_PATH, "eval-queue")34EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-results")35EVAL_REQUESTS_PATH_BACKEND = os.path.join(CACHE_PATH, "eval-queue-bk")36EVAL_RESULTS_PATH_BACKEND = os.path.join(CACHE_PATH, "eval-results-bk")37 38REFRESH_RATE = 10 * 60  # 10 min39NUM_LINES_VISUALIZE = 30040 41API = HfApi(token=TOKEN)42 43