import os from huggingface_hub import HfApi # clone / pull the lmeh eval data H4_TOKEN = os.environ.get("H4_TOKEN", None) GIT_TOKEN = os.environ.get("GIT_TOKEN", None) GIT_REPO = os.environ.get("GIT_REPO", None) REPO_ID = "HuggingFaceH4/open_llm_leaderboard" QUEUE_REPO = "lvkaokao/ld_requests" DYNAMIC_INFO_REPO = "lvkaokao/dynamic_model_information" RESULTS_REPO = "lvkaokao/ld_results" PRIVATE_QUEUE_REPO = "open-llm-leaderboard/private-requests" PRIVATE_RESULTS_REPO = "open-llm-leaderboard/private-results" IS_PUBLIC = bool(os.environ.get("IS_PUBLIC", True)) # CACHE_PATH=os.getenv("HF_HOME", ".") CACHE_PATH="./cache_hf" CACHE_GIT = "cache_git" EVAL_REQUESTS_PATH = os.path.join(CACHE_PATH, "eval-queue") EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-results") GIT_REQUESTS_PATH = os.path.join(CACHE_GIT, "requests") GIT_STATUS_PATH = os.path.join(CACHE_GIT, "status") GIT_RESULTS_PATH = os.path.join(CACHE_GIT, "results") DYNAMIC_INFO_PATH = os.path.join(CACHE_PATH, "dynamic-info") DYNAMIC_INFO_FILE_PATH = os.path.join(DYNAMIC_INFO_PATH, "model_infos.json") EVAL_REQUESTS_PATH_PRIVATE = "eval-queue-private" EVAL_RESULTS_PATH_PRIVATE = "eval-results-private" PATH_TO_COLLECTION = "lvkaokao/ld-best-models-66139bfb09f16e7347285dc2" # Rate limit variables RATE_LIMIT_PERIOD = 20 RATE_LIMIT_QUOTA = 20 HAS_HIGHER_RATE_LIMIT = ["TheBloke"] API = HfApi(token=H4_TOKEN) from git import Repo import os if not os.path.exists(CACHE_GIT): REPO = Repo.clone_from( url=GIT_REPO, to_path=CACHE_GIT, ) else: print("load from local dir.") REPO = Repo.init(CACHE_GIT) branch = REPO.active_branch.name REPO.remotes.origin.pull(branch)